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Matey-Sanz M, Gonzalez-Perez A, Casteleyn S, Granell C. Implementing and Evaluating the Timed Up and Go Test Automation Using Smartphones and Smartwatches. IEEE J Biomed Health Inform 2024; 28:6594-6605. [PMID: 39250354 DOI: 10.1109/jbhi.2024.3456169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
Physical performance tests aim to assess the physical abilities and mobility skills of individuals for various healthcare purposes. They are often driven by experts and usually performed at their practice, and therefore they are resource-intensive and time-demanding. For tests based on objective measurements (e.g., duration, repetitions), technology can be used to automate them, allowing the patients to perform the test themselves, more frequently and anywhere, while alleviating the expert from supervising the test. The well-known Timed Up and Go (TUG) test, typically used for mobility assessment, is an ideal candidate for automation, as inertial sensors (among others) can be deployed to detect the various movements constituting the test without expert supervision. To move from expert-led testing to self-administered testing, we present a mHealth system capable of automating the TUG test using a pocket-sized smartphone or a wrist smartwatch paired with a smartphone, where data from inertial sensors are used to detect the activities carried out by the patient while performing the test and compute their results in real time. All processing (i.e., data processing, machine learning-based activity inference, results calculation) takes place on the smartphone. The use of both devices to automate the TUG test was evaluated (w.r.t. accuracy, reliability and battery consumption) and mutually compared, and set off with a reference method, obtaining excellent Bland-Altman agreement results and Intraclass Correlation Coefficient reliability. Results also suggest that the smartwatch-based system performs better than the smartphone-based system.
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Brognara L, Mazzotti A, Zielli SO, Arceri A, Artioli E, Traina F, Faldini C. Wearable Technology Applications and Methods to Assess Clinical Outcomes in Foot and Ankle Disorders: Achievements and Perspectives. SENSORS (BASEL, SWITZERLAND) 2024; 24:7059. [PMID: 39517956 PMCID: PMC11548473 DOI: 10.3390/s24217059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2024] [Revised: 10/26/2024] [Accepted: 10/30/2024] [Indexed: 11/16/2024]
Abstract
Foot and ankle disorders are a very common diseases, represent a risk factor for falls in older people, and are associated with difficulty performing activities of daily living. With an increasing demand for cost-effective and high-quality clinical services, wearable technology can be strategic in extending our reach to patients with foot and ankle disorders. In recent years, wearable sensors have been increasingly utilized to assess the clinical outcomes of surgery, rehabilitation, and orthotic treatments. This article highlights recent achievements and developments in wearable sensor-based foot and ankle clinical assessment. An increasing number of studies have established the feasibility and effectiveness of wearable technology tools for foot and ankle disorders. Different methods and outcomes for feasibility studies have been introduced, such as satisfaction and efficacy in rehabilitation, surgical, and orthotic treatments. Currently, the widespread application of wearable sensors in clinical fields is hindered by a lack of robust evidence; in fact, only a few tests and analysis protocols are validated with cut-off values reported in the literature. However, nowadays, these tools are useful in quantifying clinical results before and after clinical treatments, providing useful data, also collected in real-life conditions, on the results of therapies.
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Affiliation(s)
- Lorenzo Brognara
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, 40127 Bologna, Italy;
| | - Antonio Mazzotti
- 1st Orthopaedics and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, Italy; (S.O.Z.); (A.A.); (E.A.); (F.T.); (C.F.)
- Department of Biomedical and Neuromotor Sciences (DIBINEM), Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy
| | - Simone Ottavio Zielli
- 1st Orthopaedics and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, Italy; (S.O.Z.); (A.A.); (E.A.); (F.T.); (C.F.)
- Department of Biomedical and Neuromotor Sciences (DIBINEM), Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy
| | - Alberto Arceri
- 1st Orthopaedics and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, Italy; (S.O.Z.); (A.A.); (E.A.); (F.T.); (C.F.)
- Department of Biomedical and Neuromotor Sciences (DIBINEM), Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy
| | - Elena Artioli
- 1st Orthopaedics and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, Italy; (S.O.Z.); (A.A.); (E.A.); (F.T.); (C.F.)
- Department of Biomedical and Neuromotor Sciences (DIBINEM), Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy
| | - Francesco Traina
- 1st Orthopaedics and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, Italy; (S.O.Z.); (A.A.); (E.A.); (F.T.); (C.F.)
- Department of Biomedical and Neuromotor Sciences (DIBINEM), Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy
| | - Cesare Faldini
- 1st Orthopaedics and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, Italy; (S.O.Z.); (A.A.); (E.A.); (F.T.); (C.F.)
- Department of Biomedical and Neuromotor Sciences (DIBINEM), Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy
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Tirosh O, Klonis J, Hamilton M, Olver J, Wickramasinghe N, Mckenzie D, El-Ansary D, Williams G. Smartphone Technology to Facilitate Remote Postural Balance Assessment in Acute Concussion Management: Pilot Study. SENSORS (BASEL, SWITZERLAND) 2024; 24:6870. [PMID: 39517769 PMCID: PMC11548566 DOI: 10.3390/s24216870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2024] [Revised: 09/27/2024] [Accepted: 10/24/2024] [Indexed: 11/16/2024]
Abstract
Impaired balance is a key symptom following acute concussion. Unfortunately, the recommended clinical balance assessment lacks sensitivity and discriminative ability, relying on the experience of the clinician for interpretation. The aim of this pilot study is to explore smartphone technology to remotely assess balance impairment in people with acute concussion. A smartphone app was developed to allow the clinician to connect remotely using their personal web browser to the participant's smartphone and collect motion data while instructing the participant to perform the following balance tests: standing on firm and foam surface with eyes opened and closed (FIRMEO, FIRMEC, FOAMEO, and FOAMEC). Outcome measures were processed from the raw acceleration to calculate the average acceleration magnitude from the mean and the root-mean square, with greater values indicating more sway. Eleven healthy controls (HCs) and 11 people with concussion (CON) participated. In all sway measurements, the CON group had significantly (p < 0.05) greater values when standing on a firm surface. In the FOAMEC condition, the CON group had significantly (p < 0.05) greater sway measures only in the AP direction, while significantly greater sway in all directions were found in the CON group in the FOAMEO condition. This study shows that remote balance assessment using a smartphone can discriminate between healthy controls and people with acute concussion. This technology could play an important role in concussion management to assist with determining recovery from concussions and the optimal timing for return to sport.
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Affiliation(s)
- Oren Tirosh
- School of Health and Biomedical Sciences, The Royal Melbourne Institute of Technology University, 225-245 Plenty Rd, Bundoora, VIC 3082, Australia;
- Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai 200235, China
| | - Jaymee Klonis
- Epworth Concussion Clinic, Epworth Hospital, Richmond, VIC 3121, Australia; (J.K.); (M.H.); (J.O.); (D.M.); (G.W.)
| | - Megan Hamilton
- Epworth Concussion Clinic, Epworth Hospital, Richmond, VIC 3121, Australia; (J.K.); (M.H.); (J.O.); (D.M.); (G.W.)
| | - John Olver
- Epworth Concussion Clinic, Epworth Hospital, Richmond, VIC 3121, Australia; (J.K.); (M.H.); (J.O.); (D.M.); (G.W.)
| | - Nilmini Wickramasinghe
- School of Computing, Engineering and Mathematical Sciences, La Trobe University, Bundoora, VIC 3086, Australia;
| | - Dean Mckenzie
- Epworth Concussion Clinic, Epworth Hospital, Richmond, VIC 3121, Australia; (J.K.); (M.H.); (J.O.); (D.M.); (G.W.)
| | - Doa El-Ansary
- School of Health and Biomedical Sciences, The Royal Melbourne Institute of Technology University, 225-245 Plenty Rd, Bundoora, VIC 3082, Australia;
- Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai 200235, China
| | - Gavin Williams
- Epworth Concussion Clinic, Epworth Hospital, Richmond, VIC 3121, Australia; (J.K.); (M.H.); (J.O.); (D.M.); (G.W.)
- Epworth Monash Rehabilitation Medicine Unit, University of Melbourne, Melbourne, VIC 3000, Australia
- Department of Physiotherapy, University of Melbourne, Grattan Street, Parkville, Melbourne, VIC 3010, Australia
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Kataoka Y, Ishida T, Osuka S, Takeda R, Tadano S, Yamada S, Tohyama H. Validity of Wearable Gait Analysis System for Measuring Lower-Limb Kinematics during Timed Up and Go Test. SENSORS (BASEL, SWITZERLAND) 2024; 24:6296. [PMID: 39409336 PMCID: PMC11479057 DOI: 10.3390/s24196296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Revised: 09/21/2024] [Accepted: 09/27/2024] [Indexed: 10/20/2024]
Abstract
Few studies have reported on the validity of a sensor-based lower-limb kinematics evaluation during the timed up and go (TUG) test. This study aimed to determine the validity of a wearable gait sensor system for measuring lower-limb kinematics during the TUG test. Ten young healthy participants were enrolled, and lower-limb kinematics during the TUG test were assessed using a wearable gait sensor system and a standard optical motion analysis system. The angular velocities of the hip, knee, and ankle joints in sit-to-stand and turn-to-sit phases were significantly correlated between the two motion analysis systems (R = 0.612-0.937). The peak angles and ranges of motion of hip, knee, and ankle joints in the walking-out and walking-in phases were also correlated in both systems (R = 0.528-0.924). These results indicate that the wearable gait sensor system is useful for evaluating lower-limb kinematics not only during gait, but also during the TUG test.
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Affiliation(s)
- Yoshiaki Kataoka
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan; (Y.K.); (S.O.); (S.T.); (H.T.)
- Department of Rehabilitation, Health Sciences University of Hokkaido Hospital, Sapporo 002-8072, Japan
| | - Tomoya Ishida
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan; (Y.K.); (S.O.); (S.T.); (H.T.)
| | - Satoshi Osuka
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan; (Y.K.); (S.O.); (S.T.); (H.T.)
| | - Ryo Takeda
- Faculty of Engineering, Hokkaido University, Sapporo 060-8628, Japan; (R.T.); (S.Y.)
| | - Shigeru Tadano
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan; (Y.K.); (S.O.); (S.T.); (H.T.)
| | - Satoshi Yamada
- Faculty of Engineering, Hokkaido University, Sapporo 060-8628, Japan; (R.T.); (S.Y.)
| | - Harukazu Tohyama
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan; (Y.K.); (S.O.); (S.T.); (H.T.)
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McCreath Frangakis AL, Lemaire ED, Burger H, Baddour N. L Test Subtask Segmentation for Lower-Limb Amputees Using a Random Forest Algorithm. SENSORS (BASEL, SWITZERLAND) 2024; 24:4953. [PMID: 39124000 PMCID: PMC11314735 DOI: 10.3390/s24154953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Revised: 07/26/2024] [Accepted: 07/27/2024] [Indexed: 08/12/2024]
Abstract
Functional mobility tests, such as the L test of functional mobility, are recommended to provide clinicians with information regarding the mobility progress of lower-limb amputees. Smartphone inertial sensors have been used to perform subtask segmentation on functional mobility tests, providing further clinically useful measures such as fall risk. However, L test subtask segmentation rule-based algorithms developed for able-bodied individuals have not produced sufficiently acceptable results when tested with lower-limb amputee data. In this paper, a random forest machine learning model was trained to segment subtasks of the L test for application to lower-limb amputees. The model was trained with 105 trials completed by able-bodied participants and 25 trials completed by lower-limb amputee participants and tested using a leave-one-out method with lower-limb amputees. This algorithm successfully classified subtasks within a one-foot strike for most lower-limb amputee participants. The algorithm produced acceptable results to enhance clinician understanding of a person's mobility status (>85% accuracy, >75% sensitivity, >95% specificity).
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Affiliation(s)
| | - Edward D. Lemaire
- Faculty of Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada;
| | - Helena Burger
- University Rehabilitation Institute, University of Ljubljana, 1000 Ljubljana, Slovenia;
- Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Natalie Baddour
- Department of Mechanical Engineering, Faculty of Engineering, University of Ottawa, Ottawa, ON K1N 6N5, Canada;
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Ting KC, Lin YC, Chan CT, Tu TY, Shih CC, Liu KC, Tsao Y. Inertial Measurement Unit-Based Romberg Test for Assessing Adults With Vestibular Hypofunction. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2023; 12:245-255. [PMID: 38196821 PMCID: PMC10776102 DOI: 10.1109/jtehm.2023.3334238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 08/22/2023] [Accepted: 10/18/2023] [Indexed: 01/11/2024]
Abstract
This work aims to explore the utility of wearable inertial measurement units (IMUs) for quantifying movement in Romberg tests and investigate the extent of movement in adults with vestibular hypofunction (VH). A cross-sectional study was conducted at an academic tertiary medical center between March 2021 and April 2022. Adults diagnosed with unilateral vestibular hypofunction (UVH) or bilateral vestibular hypofunction (BVH) were enrolled in the VH group. Healthy controls (HCs) were recruited from community or outpatient clinics. The IMU-based instrumented Romberg and tandem Romberg tests on the floor were applied to both groups. The primary outcomes were kinematic body metrics (maximum acceleration [ACC], mean ACC, root mean square [RMS] of ACC, and mean sway velocity [MV]) along the medio-lateral (ML), cranio-caudal (CC), and antero-posterior (AP) axes. A total of 31 VH participants (mean age, 33.48 [SD 7.68] years; 19 [61%] female) and 31 HCs (mean age, 30.65 [SD 5.89] years; 18 [58%] female) were recruited. During the eyes-closed portion of the Romberg test, VH participants demonstrated significantly higher maximum ACC and increased RMS of ACC in head movement, as well as higher maximum ACC in pelvic movement along the ML axis. In the same test condition, individuals with BVH exhibited notably higher maximum ACC and RMS of ACC along the ML axis in head and pelvic movements compared with HCs. Additionally, BVH participants exhibited markedly increased maximum ACC along the ML axis in head movement during the eyes-open portion of the tandem Romberg test. Conversely, no significant differences were found between UVH participants and HCs in the assessed parameters. The instrumented Romberg and tandem Romberg tests characterized the kinematic differences in head, pelvis, and ankle movement between VH and healthy adults. The findings suggest that these kinematic body metrics can be useful for screening BVH and can provide goals for vestibular rehabilitation.
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Affiliation(s)
- Kuan-Chung Ting
- Department of Otolaryngology-Head and Neck SurgeryTaipei Veterans General HospitalTaipei11217Taiwan
- Institute of Clinical Medicine, National Yang Ming Chiao Tung UniversityTaipei11221Taiwan
- School of MedicineNational Yang Ming Chiao Tung UniversityTaipei11221Taiwan
| | - Yu-Chieh Lin
- Department of Biomedical EngineeringNational Yang Ming Chiao Tung UniversityTaipei11221Taiwan
| | - Chia-Tai Chan
- Department of Biomedical EngineeringNational Yang Ming Chiao Tung UniversityTaipei11221Taiwan
| | - Tzong-Yang Tu
- Department of Otolaryngology-Head and Neck SurgeryTaipei Veterans General HospitalTaipei11217Taiwan
| | - Chun-Che Shih
- Institute of Clinical Medicine, National Yang Ming Chiao Tung UniversityTaipei11221Taiwan
- Division of Cardiovascular SurgeryTaipei Municipal Wanfang HospitalTaipei11608Taiwan
- Taipei Heart Institute, Taipei Medical UniversityTaipei11013Taiwan
| | - Kai-Chun Liu
- Research Center for Information Technology InnovationAcademia SinicaTaipei11529Taiwan
| | - Yu Tsao
- Research Center for Information Technology InnovationAcademia SinicaTaipei11529Taiwan
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Duncan L, Zhu S, Pergolotti M, Giri S, Salsabili H, Faezipour M, Ostadabbas S, Mirbozorgi SA. Camera-Based Short Physical Performance Battery and Timed Up and Go Assessment for Older Adults With Cancer. IEEE Trans Biomed Eng 2023; 70:2529-2539. [PMID: 37028022 DOI: 10.1109/tbme.2023.3253061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
Abstract
This paper presents an automatic camera-based device to monitor and evaluate the gait speed, standing balance, and 5 times sit-stand (5TSS) tests of the Short Physical Performance Battery (SPPB) and the Timed Up and Go (TUG) test. The proposed design measures and calculates the parameters of the SPPB tests automatically. The SPPB data can be used for physical performance assessment of older patients under cancer treatment. This stand-alone device has a Raspberry Pi (RPi) computer, three cameras, and two DC motors. The left and right cameras are used for gait speed tests. The center camera is used for standing balance, 5TSS, and TUG tests and for angle positioning of the camera platform toward the subject using DC motors by turning the camera left/right and tilting it up/down. The key algorithm for operating the proposed system is developed using Channel and Spatial Reliability Tracking in the cv2 module in Python. Graphical User Interfaces (GUIs) in the RPi are developed to run tests and adjust cameras, controlled remotely via smartphone and its Wi-Fi hotspot. We have tested the implemented camera setup prototype and extracted all SPPB and TUG parameters by conducting several experiments on a human subject population of 8 volunteers (male and female, light and dark complexions) in 69 test runs. The measured data and calculated outputs of the system consist of tests of gait speed (0.041 to 1.92 m/s with average accuracy of >95%), and standing balance, 5TSS, TUG, all with average time accuracy of >97%.
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Wallis-Lang K, Bastrom TP, Boutelle KE, Wagle A, Pennock AT, Edmonds EW. Assessment of Thresholds for Clinically Relevant Change in the Pediatric/Adolescent Shoulder Survey After Shoulder Instability Surgery: Factors Associated With Meaningful Improvement in Outcomes. Orthop J Sports Med 2023; 11:23259671231196943. [PMID: 37786475 PMCID: PMC10541762 DOI: 10.1177/23259671231196943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 05/04/2023] [Indexed: 10/04/2023] Open
Abstract
Background The pediatric/adolescent shoulder survey (PASS) score is a subjective measure of shoulder symptomology in younger patients. Purpose To establish the minimal clinically important difference (MCID) and minimal detectable change (MDC) for the PASS score in adolescents after surgical treatment for shoulder instability. Study Design Case series; Level of evidence, 4. Methods Included were patients aged 12.5 to 23 years who underwent surgical treatment for shoulder instability and who had completed PASS forms preoperatively and at 3 months postoperatively. The MCID was established using an anchor-based approach, with the Single Assessment Numeric Evaluation (SANE) and shortened version of the Disabilities of the Arm, Shoulder and Hand (QuickDASH) as anchors. Change in PASS score between anchor groups was determined using receiver operating characteristic curve analysis. MDC with 90% confidence (MDC90) was also calculated. Range of motion and strength data at 3-month follow-up were evaluated to identify the optimal postoperative PASS score. Factors associated with improvement in PASS score beyond the MDC90 and MCID were determined in a subset of patients with ≥6-month follow-up data. Results A total of 95 patients were included. The mean PASS score improved significantly from preoperatively to postoperatively (57 ± 15 to 75 ± 16; P < .001). The anchor-based MCID ranged from 12.5 to 13.2 points, with an area under the receiver operating characteristic (AUC) curve of 0.87 for the SANE and 0.99 for the QuickDASH. The MDC90 was 16.5 points. The optimal PASS score at 3 months after surgery was ≥85 (AUC, 0.66). Shorter duration of symptoms, lower preoperative forward elevation, and higher preoperative external rotation were associated with improvement in PASS score above the MDC90 and/or MCID for the subset of patients (n = 25) with ≥6-month follow-up data. Increased number of suture anchors, less preoperative external rotation deficit, and number of previous dislocations had a moderate effect on improvement in outcomes. Conclusion A postoperative increase in PASS score of ≥16.5 points had a 90% chance of being a true-positive change, while a score change of approximately 13 points was likely clinically relevant. The optimal PASS score after surgery was ≥85. Shorter duration of symptoms, preoperative range of motion, number of surgical anchors, and number of previous dislocations were associated with achieving a clinically relevant improvement in PASS score at minimum 6 months postoperatively.
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Affiliation(s)
| | - Tracey P. Bastrom
- Department of Orthopedics, Rady Children's Hospital, San Diego, California, USA
| | - Kelly E. Boutelle
- Department of Orthopedics, Rady Children's Hospital, San Diego, California, USA
| | - Abigail Wagle
- Department of Orthopedics, Rady Children's Hospital, San Diego, California, USA
| | - Andrew T. Pennock
- University of California, San Diego, San Diego, California, USA
- Department of Orthopedics, Rady Children's Hospital, San Diego, California, USA
| | - Eric W. Edmonds
- University of California, San Diego, San Diego, California, USA
- Department of Orthopedics, Rady Children's Hospital, San Diego, California, USA
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Kamnardsiri T, Thawinchai N, Parameyong A, Pholjaroen P, Wonglangka K, Prupetkaew P, Boripuntakul S. Conventional video-based system for measuring the subtask speed of the Timed Up and Go Test in older adults: Validity and reliability study. PLoS One 2023; 18:e0286574. [PMID: 37267315 DOI: 10.1371/journal.pone.0286574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 05/18/2023] [Indexed: 06/04/2023] Open
Abstract
The Timed Up and Go Test (TUG) is a simple fall risk screening test that covers basic functional movement; thus, quantifying the subtask movement ability may provide a clinical utility. The video-based system allows individual's movement characteristics assessment. This study aimed to investigate the concurrent validity and test-retest reliability of the video-based system for assessing the movement speed of TUG subtasks among older adults. Twenty older adults participated in the validity study, whilst ten older adults participated in the reliability study. Participant's movement speed in each subtask of the TUG under comfortable and fast speed conditions over two sessions was measured. Pearson correlation coefficient was used to identify the validity of the video-based system compared to the motion analysis system. Intraclass correlation coefficient (ICC3,2) was used to determine the reliability of the video-based system. The Bland-Altman plots were used to quantify the agreement between the two measurement systems and two repeatable sessions. The validity analysis demonstrated a moderate to very high relationship in all TUG subtask movement speeds between the two systems under the comfortable speed (r = 0.672-0.906, p < 0.05) and a moderate to high relationship under the fast speed (r = 0.681-0.876, p < 0.05). The reliability of the video-based system was good to excellent for all subtask movement speeds in both the comfortable speed (ICCs = 0.851-0.967, p < 0.05) and fast speed (ICCs = 0.720-0.979, p < 0.05). The Bland-Altman analyses showed that almost all mean differences of the subtask speed of the TUG were close to zero, within 95% limits of agreement, and symmetrical distribution of scatter plots. The video-based system was a valid and reliable tool that may be useful in measuring the subtask movement speed of TUG among healthy older adults.
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Affiliation(s)
- Teerawat Kamnardsiri
- Department of Digital Game, College of Arts, Media and Technology, Chiang Mai University, Chiang Mai, Thailand
- Research Group in Informatics for Well-being Society, Chiang Mai University, Chiang Mai, Thailand
| | - Nuanlaor Thawinchai
- Faculty of Associated Medical Sciences, Department of Physical Therapy, Chiang Mai University, Chiang Mai, Thailand
| | - Arisa Parameyong
- Faculty of Associated Medical Sciences, Department of Physical Therapy, Chiang Mai University, Chiang Mai, Thailand
| | - Pim Pholjaroen
- Faculty of Associated Medical Sciences, Department of Physical Therapy, Chiang Mai University, Chiang Mai, Thailand
| | - Khanittha Wonglangka
- Faculty of Associated Medical Sciences, Department of Physical Therapy, Chiang Mai University, Chiang Mai, Thailand
| | - Paphawee Prupetkaew
- Faculty of Associated Medical Sciences, Department of Physical Therapy, Chiang Mai University, Chiang Mai, Thailand
| | - Sirinun Boripuntakul
- Research Group in Informatics for Well-being Society, Chiang Mai University, Chiang Mai, Thailand
- Faculty of Associated Medical Sciences, Department of Physical Therapy, Chiang Mai University, Chiang Mai, Thailand
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Marshall CJ, Ganderton C, Feltham A, El-Ansary D, Pranata A, O'Donnell J, Takla A, Tran P, Wickramasinghe N, Tirosh O. Smartphone Technology to Remotely Measure Postural Sway during Double- and Single-Leg Squats in Adults with Femoroacetabular Impingement and Those with No Hip Pain. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23115101. [PMID: 37299827 DOI: 10.3390/s23115101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 05/21/2023] [Accepted: 05/24/2023] [Indexed: 06/12/2023]
Abstract
BACKGROUND The COVID-19 pandemic has accelerated the demand for utilising telehealth as a major mode of healthcare delivery, with increasing interest in the use of tele-platforms for remote patient assessment. In this context, the use of smartphone technology to measure squat performance in people with and without femoroacetabular impingement (FAI) syndrome has not been reported yet. We developed a novel smartphone application, the TelePhysio app, which allows the clinician to remotely connect to the patient's device and measure their squat performance in real time using the smartphone inertial sensors. The aim of this study was to investigate the association and test-retest reliability of the TelePhysio app in measuring postural sway performance during a double-leg (DLS) and single-leg (SLS) squat task. In addition, the study investigated the ability of TelePhysio to detect differences in DLS and SLS performance between people with FAI and without hip pain. METHODS A total of 30 healthy (nfemales = 12) young adults and 10 adults (nfemales = 2) with diagnosed FAI syndrome participated in the study. Healthy participants performed DLS and SLS on force plates in our laboratory, and remotely in their homes using the TelePhysio smartphone application. Sway measurements were compared using the centre of pressure (CoP) and smartphone inertial sensor data. A total of 10 participants with FAI (nfemales = 2) performed the squat assessments remotely. Four sway measurements in each axis (x, y, and z) were computed from the TelePhysio inertial sensors: (1) average acceleration magnitude from the mean (aam), (2) root-mean-square acceleration (rms), (3) range acceleration (r), and (4) approximate entropy (apen), with lower values indicating that the movement is more regular, repetitive, and predictable. Differences in TelePhysio squat sway data were compared between DLS and SLS, and between healthy and FAI adults, using analysis of variance with significance set at 0.05. RESULTS The TelePhysio aam measurements on the x- and y-axes had significant large correlations with the CoP measurements (r = 0.56 and r = 0.71, respectively). The TelePhysio aam measurements demonstrated moderate to substantial between-session reliability values of 0.73 (95% CI 0.62-0.81), 0.85 (95% CI 0.79-0.91), and 0.73 (95% CI 0.62-0.82) for aamx, aamy, and aamz, respectively. The DLS of the FAI participants showed significantly lower aam and apen values in the medio-lateral direction compared to the healthy DLS, healthy SLS, and FAI SLS groups (aam = 0.13, 0.19, 0.29, and 0.29, respectively; and apen = 0.33, 0.45, 0.52, and 0.48, respectively). In the anterior-posterior direction, healthy DLS showed significantly greater aam values compared to the healthy SLS, FAI DLS, and FAI SLS groups (1.26, 0.61, 0.68, and 0.35, respectively). CONCLUSIONS The TelePhysio app is a valid and reliable method of measuring postural control during DLS and SLS tasks. The application is capable of distinguishing performance levels between DLS and SLS tasks, and between healthy and FAI young adults. The DLS task is sufficient to distinguish the level of performance between healthy and FAI adults. This study validates the use of smartphone technology as a tele-assessment clinical tool for remote squat assessment.
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Affiliation(s)
- Charlotte J Marshall
- School of Health Sciences, Swinburne University of Technology, Hawthorn 3122, Australia
| | - Charlotte Ganderton
- School of Health Sciences, Swinburne University of Technology, Hawthorn 3122, Australia
- School of Clinical Medicine, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
| | - Adam Feltham
- School of Health Sciences, Swinburne University of Technology, Hawthorn 3122, Australia
| | - Doa El-Ansary
- School of Clinical Medicine, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
- Department of Surgery, School of Medicine, University of Melbourne, Parkville 3052, Australia
- School of Health and Biomedical Sciences, RMIT University, Bundoora 3083, Australia
| | - Adrian Pranata
- School of Health Sciences, Swinburne University of Technology, Hawthorn 3122, Australia
- School of Clinical Medicine, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
| | - John O'Donnell
- Hip Arthroscopy Australia, 21 Erin Street, Richmond 3121, Australia
| | - Amir Takla
- Hip Arthroscopy Australia, 21 Erin Street, Richmond 3121, Australia
| | - Phong Tran
- School of Health Sciences, Swinburne University of Technology, Hawthorn 3122, Australia
- Department of Surgery, School of Medicine, University of Melbourne, Parkville 3052, Australia
- Department of Orthopaedic Surgery, Western Health, Footscray Hospital, Footscray 3011, Australia
| | | | - Oren Tirosh
- School of Health Sciences, Swinburne University of Technology, Hawthorn 3122, Australia
- School of Clinical Medicine, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
- Department of Orthopaedic Surgery, Western Health, Footscray Hospital, Footscray 3011, Australia
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Ortega-Bastidas P, Gómez B, Aqueveque P, Luarte-Martínez S, Cano-de-la-Cuerda R. Instrumented Timed Up and Go Test (iTUG)-More Than Assessing Time to Predict Falls: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:3426. [PMID: 37050485 PMCID: PMC10098780 DOI: 10.3390/s23073426] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 03/17/2023] [Accepted: 03/20/2023] [Indexed: 06/19/2023]
Abstract
The Timed Up and Go (TUG) test is a widely used tool for assessing the risk of falls in older adults. However, to increase the test's predictive value, the instrumented Timed Up and Go (iTUG) test has been developed, incorporating different technological approaches. This systematic review aims to explore the evidence of the technological proposal for the segmentation and analysis of iTUG in elderlies with or without pathologies. A search was conducted in five major databases, following PRISMA guidelines. The review included 40 studies that met the eligibility criteria. The most used technology was inertial sensors (75% of the studies), with healthy elderlies (35%) and elderlies with Parkinson's disease (32.5%) being the most analyzed participants. In total, 97.5% of the studies applied automatic segmentation using rule-based algorithms. The iTUG test offers an economical and accessible alternative to increase the predictive value of TUG, identifying different variables, and can be used in clinical, community, and home settings.
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Affiliation(s)
- Paulina Ortega-Bastidas
- Health Sciences PhD Programme, International Doctoral School, Universidad Rey Juan Carlos, 28922 Madrid, Spain
- Kinesiology Department, Faculty of Medicine, Universidad de Concepción, Concepción, 151 Janequeo St., Concepcion 4030000, Chile
| | - Britam Gómez
- Biomedical Engineering, Faculty of Engineering, Universidad de Santiago de Chile, Libertador Bernardo O’Higgins Av., Santiago 9170022, Chile
| | - Pablo Aqueveque
- Department of Electrical Engineering, Faculty of Engineering, Universidad de Concepción, 219 Edmundo Larenas St., Concepción 4030000, Chile
| | - Soledad Luarte-Martínez
- Kinesiology Department, Faculty of Medicine, Universidad de Concepción, Concepción, 151 Janequeo St., Concepcion 4030000, Chile
| | - Roberto Cano-de-la-Cuerda
- Physiotherapy, Occupational Therapy, Rehabilitation and Physical Medicine Department, Universidad Rey Juan Carlos, 28922 Madrid, Spain
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12
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Subtask Segmentation Methods of the Timed Up and Go Test and L Test Using Inertial Measurement Units—A Scoping Review. INFORMATION 2023. [DOI: 10.3390/info14020127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023] Open
Abstract
The Timed Up and Go test (TUG) and L Test are functional mobility tests that allow healthcare providers to assess a person’s balance and fall risk. Segmenting these mobility tests into their respective subtasks, using sensors, can provide further and more precise information on mobility status. To identify and compare current methods for subtask segmentation using inertial sensor data, a scoping review of the literature was conducted using PubMed, Scopus, and Google Scholar. Articles were identified that described subtask segmentation methods for the TUG and L Test using only inertial sensor data. The filtering method, ground truth estimation device, demographic, and algorithm type were compared. One article segmenting the L Test and 24 articles segmenting the TUG met the criteria. The articles were published between 2008 and 2022. Five studies used a mobile smart device’s inertial measurement system, while 20 studies used a varying number of external inertial measurement units. Healthy adults, people with Parkinson’s Disease, and the elderly were the most common demographics. A universally accepted method for segmenting the TUG test and the L Test has yet to be published. Angular velocity in the vertical and mediolateral directions were common signals for subtask differentiation. Increasing sample sizes and furthering the comparison of segmentation methods with the same test sets will allow us to expand the knowledge generated from these clinically accessible tests.
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13
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Kataoka Y, Saito Y, Takeda R, Ishida T, Tadano S, Suzuki T, Nakamura K, Nakata A, Osuka S, Yamada S, Samukawa M, Tohyama H. Evaluation of Lower-Limb Kinematics during Timed Up and Go (TUG) Test in Subjects with Locomotive Syndrome (LS) Using Wearable Gait Sensors (H-Gait System). SENSORS (BASEL, SWITZERLAND) 2023; 23:s23020687. [PMID: 36679484 PMCID: PMC9865281 DOI: 10.3390/s23020687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/31/2022] [Accepted: 01/04/2023] [Indexed: 05/05/2023]
Abstract
Few studies have dealt with lower-limb kinematics during the timed up and go (TUG) test in subjects with locomotive syndrome (LS). This study aimed to evaluate the characteristics of lower-limb kinematics during the TUG test in subjects with LS using the wearable sensor-based H-Gait system. A total of 140 participants were divided into the non-LS (n = 28), the LS-stage 1 (n = 78), and LS-stage 2 (n = 34) groups based on the LS risk test. Compared with the non-LS group, the LS-stage 1 and LS-stage 2 groups showed significantly smaller angular velocity of hip and knee extension during the sit-to-stand phase. The LS-stage 2 group showed significantly smaller peak angles of hip extension and flexion during the walking-out phase compared to the non-LS group. These findings indicate that the evaluation of the lower-limb kinematics during the TUG test using the H-Gait system is highly sensitive to detect LS, compared with the evaluation of the lower-limb kinematics when simply walking.
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Affiliation(s)
- Yoshiaki Kataoka
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan
- Department of Rehabilitation, Health Sciences University of Hokkaido Hospital, Sapporo 002-8072, Japan
| | - Yuki Saito
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan
| | - Ryo Takeda
- Faculty of Engineering, Hokkaido University, Sapporo 060-8628, Japan
| | - Tomoya Ishida
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan
| | - Shigeru Tadano
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan
| | - Teppei Suzuki
- Iwamizawa Campus Midorigaoka, Hokkaido University of Education, 2-34, Iwamizawa 068-864, Japan
| | - Kentaro Nakamura
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan
| | - Akimi Nakata
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan
| | - Satoshi Osuka
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan
| | - Satoshi Yamada
- Faculty of Engineering, Hokkaido University, Sapporo 060-8628, Japan
| | - Mina Samukawa
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan
| | - Harukazu Tohyama
- Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan
- Correspondence: ; Tel.: +81-11-706-3393
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14
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Meigal AY, Gerasimova-Meigal LI, Reginya SA, Soloviev AV, Moschevikin AP. Gait Characteristics Analyzed with Smartphone IMU Sensors in Subjects with Parkinsonism under the Conditions of "Dry" Immersion. SENSORS (BASEL, SWITZERLAND) 2022; 22:7915. [PMID: 36298272 PMCID: PMC9611186 DOI: 10.3390/s22207915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/23/2022] [Accepted: 10/14/2022] [Indexed: 06/16/2023]
Abstract
Parkinson's disease (PD) is increasingly being studied using science-intensive methods due to economic, medical, rehabilitation and social reasons. Wearable sensors and Internet of Things-enabled technologies look promising for monitoring motor activity and gait in PD patients. In this study, we sought to evaluate gait characteristics by analyzing the accelerometer signal received from a smartphone attached to the head during an extended TUG test, before and after single and repeated sessions of terrestrial microgravity modeled with the condition of "dry" immersion (DI) in five subjects with PD. The accelerometer signal from IMU during walking phases of the TUG test allowed for the recognition and characterization of up to 35 steps. In some patients with PD, unusually long steps have been identified, which could potentially have diagnostic value. It was found that after one DI session, stepping did not change, though in one subject it significantly improved (cadence, heel strike and step length). After a course of DI sessions, some characteristics of the TUG test improved significantly. In conclusion, the use of accelerometer signals received from a smartphone IMU looks promising for the creation of an IoT-enabled system to monitor gait in subjects with PD.
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Affiliation(s)
- Alexander Y. Meigal
- Medical Institute, Petrozavodsk State University, 33, Lenina pr., 185910 Petrozavodsk, Russia
| | | | - Sergey A. Reginya
- Physical-Technical Institute, Petrozavodsk State University, 33, Lenina pr., 185910 Petrozavodsk, Russia
| | - Alexey V. Soloviev
- Physical-Technical Institute, Petrozavodsk State University, 33, Lenina pr., 185910 Petrozavodsk, Russia
| | - Alex P. Moschevikin
- Physical-Technical Institute, Petrozavodsk State University, 33, Lenina pr., 185910 Petrozavodsk, Russia
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THOMAS JACOBM, KOLLOCK ROGERO. The Reliability of Three-Dimensional Inertial Measurement Units in Capturing Lower-Body Joint Kinematics during Single-Leg Landing Tasks. INTERNATIONAL JOURNAL OF EXERCISE SCIENCE 2022; 15:1306-1316. [PMID: 36582517 PMCID: PMC9762242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
3-D inertial measurement units (IMUs) have advantages over other types of motion capture systems, as IMUs cannot be obstructed by equipment and gear. Therefore, the purpose of this study was to assess the reliability of IMUs in measuring joint angles at the hip, knee, and ankle during two types of single-leg landings: 1) drop-landing (DL) and 2) leap-landing (LL). Nineteen subjects, both males (n = 9, 21.88 ± 1.64 yrs, 178.36 ± 9.68 cm, 185.68 ± 16.63 kg) and females (n = 11, 22.45 ± 4.32 yrs, 171.57 ± 6.55 cm, 70.95 ± 14.99 kg) participated in this study. Participants performed three trials of both tasks. The DL required the participant to drop onto their dominant leg from a 30 cm box onto force plate. The LL task required participants to leap over a 20 cm hurdle onto the force plate. ICC values and SEM calculations were used to assess the IMU's reliability. Overall, IMUs displayed fair-to-excellent reliability for both tasks (ICC = 0.442-0.962), aside from ankle inversion (ICC = 0.290) & ankle abduction (ICC = 0.216) at initial ground contact and ankle abduction (ICC = 0.234) at maximum vertical ground reaction force, both during the LL task. IMUs can be a reliable measurement tool for lower extremity motion during dynamic landing, so long as factors related to reliability at the ankle are considered.
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16
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Choi Y, Bae Y, Cha B, Ryu J. Deep Learning-Based Subtask Segmentation of Timed Up-and-Go Test Using RGB-D Cameras. SENSORS (BASEL, SWITZERLAND) 2022; 22:6323. [PMID: 36080782 PMCID: PMC9459743 DOI: 10.3390/s22176323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 08/12/2022] [Accepted: 08/18/2022] [Indexed: 06/15/2023]
Abstract
The timed up-and-go (TUG) test is an efficient way to evaluate an individual's basic functional mobility, such as standing up, walking, turning around, and sitting back. The total completion time of the TUG test is a metric indicating an individual's overall mobility. Moreover, the fine-grained consumption time of the individual subtasks in the TUG test may provide important clinical information, such as elapsed time and speed of each TUG subtask, which may not only assist professionals in clinical interventions but also distinguish the functional recovery of patients. To perform more accurate, efficient, robust, and objective tests, this paper proposes a novel deep learning-based subtask segmentation of the TUG test using a dilated temporal convolutional network with a single RGB-D camera. Evaluation with three different subject groups (healthy young, healthy adult, stroke patients) showed that the proposed method demonstrated better generality and achieved a significantly higher and more robust performance (healthy young = 95.458%, healthy adult = 94.525%, stroke = 93.578%) than the existing rule-based and artificial neural network-based subtask segmentation methods. Additionally, the results indicated that the input from the pelvis alone achieved the best accuracy among many other single inputs or combinations of inputs, which allows a real-time inference (approximately 15 Hz) in edge devices, such as smartphones.
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17
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Ko JB, Hong JS, Shin YS, Kim KB. Machine Learning-Based Predicted Age of the Elderly on the Instrumented Timed Up and Go Test and Six-Minute Walk Test. SENSORS (BASEL, SWITZERLAND) 2022; 22:5957. [PMID: 36015714 PMCID: PMC9413258 DOI: 10.3390/s22165957] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 08/08/2022] [Accepted: 08/08/2022] [Indexed: 06/15/2023]
Abstract
A decrease in dynamic balance ability (DBA) in the elderly is closely associated with aging. Various studies have investigated different methods to quantify the DBA in the elderly through DBA evaluation methods such as the timed up and go test (TUG) and the six-minute walk test (6MWT), applying the G-Walk wearable system. However, these methods have generally been difficult for the elderly to intuitively understand. The goal of this study was thus to generate a regression model based on machine learning (ML) to predict the age of the elderly as a familiar indicator. The model was based on inertial measurement unit (IMU) data as part of the DBA evaluation, and the performance of the model was comparatively analyzed with respect to age prediction based on the IMU data of the TUG test and the 6MWT. The DBA evaluation used the TUG test and the 6MWT performed by 136 elderly participants. When performing the TUG test and the 6MWT, a single IMU was attached to the second lumbar spine of the participant, and the three-dimensional linear acceleration and gyroscope data were collected. The features used in the ML-based regression model included the gait symmetry parameters and the harmonic ratio applied in quantifying the DBA, in addition to the features of description statistics for IMU signals. The feature set was differentiated between the TUG test and the 6MWT, and the performance of the regression model was comparatively analyzed based on the feature sets. The XGBoost algorithm was used to train the regression model. Comparison of the regression model performance according to the TUG test and 6MWT feature sets showed that the performance was best for the model using all features of the TUG test and the 6MWT. This indicated that the evaluation of DBA in the elderly should apply the TUG test and the 6MWT concomitantly for more accurate predictions. The findings in this study provide basic data for the development of a DBA monitoring system for the elderly.
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Affiliation(s)
| | | | | | - Kwang Bok Kim
- Correspondence: ; Tel.: +82-41-589-8465; Fax: +82-41-589-8640
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18
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Reliability Study of Inertial Sensors LIS2DH12 Compared to ActiGraph GT9X: Based on Free Code. J Pers Med 2022; 12:jpm12050749. [PMID: 35629171 PMCID: PMC9147434 DOI: 10.3390/jpm12050749] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 04/28/2022] [Accepted: 05/03/2022] [Indexed: 12/04/2022] Open
Abstract
The study’s purpose was to assess the reliability of the LIS2DH12 in two different positions, using the commercial sensor Actigraph GT9X as a reference instrument. Five participants completed two gait tests on a treadmill. Firstly, both sensors were worn on the wrist and around the thigh. Each test consisted of a 1 min walk for participants to become accustomed to the treadmill, followed by a 2 min trial at ten pre-set speeds. Data from both sensors were collected in real-time. Intraclass correlation coefficient (ICC) was used to evaluate the equality of characteristics obtained by both sensors: maximum peaks, minimum peaks, and the mean of the complete signal (sequence of acceleration values along the time) by each axis and speed were extracted to evaluate the equality of characteristics obtained with LIS2DH12 compared to Actigraph. Intraclass correlation coefficient (ICC) was extracted, and a standard deviation of the mean was obtained from the data. Our results show that LIS2DH12 measurements present more reliability than Actigraph GT9X, ICC > 0.8 at three axes. This study concludes that LIS2DH12 is as reliable and accurate as Actigraph GT9X Link and, therefore, would be a suitable tool for future kinematic studies.
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19
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Weston AR, Loyd BJ, Taylor C, Hoppes C, Dibble LE. Head and Trunk Kinematics during Activities of Daily Living with and without Mechanical Restriction of Cervical Motion. SENSORS (BASEL, SWITZERLAND) 2022; 22:3071. [PMID: 35459056 PMCID: PMC9026113 DOI: 10.3390/s22083071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/06/2022] [Accepted: 04/12/2022] [Indexed: 11/16/2022]
Abstract
Alterations in head and trunk kinematics during activities of daily living can be difficult to recognize and quantify with visual observation. Incorporating wearable sensors allows for accurate and measurable assessment of movement. The aim of this study was to determine the ability of wearable sensors and data processing algorithms to discern motion restrictions during activities of daily living. Accelerometer data was collected with wearable sensors from 10 healthy adults (age 39.5 ± 12.47) as they performed daily living simulated tasks: coin pick up (pitch plane task), don/doff jacket (yaw plane task), self-paced community ambulation task [CAT] (pitch and yaw plane task) without and with a rigid cervical collar. Paired t-tests were used to discern differences between non-restricted (no collared) performance and restricted (collared) performance of tasks. Significant differences in head rotational velocity (jacket p = 0.03, CAT-pitch p < 0.001, CAT-yaw p < 0.001), head rotational amplitude (coin p = 0.03, CAT-pitch p < 0.001, CAT-yaw p < 0.001), trunk rotational amplitude (jacket p = 0.01, CAT-yaw p = 0.005), and head−trunk coupling (jacket p = 0.007, CAT-yaw p = 0.003) were captured by wearable sensors between the two conditions. Alterations in turning movement were detected at the head and trunk during daily living tasks. These results support the ecological validity of using wearable sensors to quantify movement alterations during real-world scenarios.
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Affiliation(s)
- Angela R. Weston
- Department of Physical Therapy and Athletic Training, University of Utah, 520 Wakara Way, Salt Lake City, UT 84108, USA;
| | - Brian J. Loyd
- Department of Physical Therapy and Rehabilitation Sciences, University of Montana, 32 Campus Dr., Missoula, MT 59812, USA;
| | - Carolyn Taylor
- Department of Orthopedics, University of Utah, 590 Wakara Way, Salt Lake City, UT 84108, USA;
| | - Carrie Hoppes
- Army Baylor University Doctoral Program in Physical Therapy, U.S. Army Medical Center of Excellence, 3630 Stanley Road, San Antonio, TX 78234, USA;
| | - Leland E. Dibble
- Department of Physical Therapy and Athletic Training, University of Utah, 520 Wakara Way, Salt Lake City, UT 84108, USA;
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High Specificity of Single Inertial Sensor-Supplemented Timed Up and Go Test for Assessing Fall Risk in Elderly Nursing Home Residents. SENSORS 2022; 22:s22062339. [PMID: 35336510 PMCID: PMC8950330 DOI: 10.3390/s22062339] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 02/04/2023]
Abstract
The Timed Up and Go test (TUG) is commonly used to estimate the fall risk in the elderly. Several ways to improve the predictive accuracy of TUG (cameras, multiple sensors, other clinical tests) have already been proposed. Here, we added a single wearable inertial measurement unit (IMU) to capture the residents’ body center-of-mass kinematics in view of improving TUG’s predictive accuracy. The aim is to find out which kinematic variables and residents’ characteristics are relevant for distinguishing faller from non-faller patients. Data were collected in 73 nursing home residents with the IMU placed on the lower back. Acceleration and angular velocity time series were analyzed during different subtasks of the TUG. Multiple logistic regressions showed that total time required, maximum angular velocity at the first half-turn, gender, and use of a walking aid were the parameters leading to the best predictive abilities of fall risk. The predictive accuracy of the proposed new test, called i + TUG, reached a value of 74.0%, with a specificity of 95.9% and a sensitivity of 29.2%. By adding a single wearable IMU to TUG, an accurate and highly specific test is therefore obtained. This method is quick, easy to perform and inexpensive. We recommend to integrate it into daily clinical practice in nursing homes.
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Instrumented Timed Up and Go Test Using Inertial Sensors from Consumer Wearable Devices. Artif Intell Med 2022. [DOI: 10.1007/978-3-031-09342-5_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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22
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Ko JB, Kim KB, Shin YS, Han H, Han SK, Jung DY, Hong JS. Predicting Sarcopenia of Female Elderly from Physical Activity Performance Measurement Using Machine Learning Classifiers. Clin Interv Aging 2021; 16:1723-1733. [PMID: 34611396 PMCID: PMC8485854 DOI: 10.2147/cia.s323761] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 09/01/2021] [Indexed: 11/23/2022] Open
Abstract
Purpose Sarcopenia is a symptom in which muscle mass decreases due to decreasing in the number of muscle fibers and muscle cross-sectional area as aging. This study aimed to develop a machine learning classification model for predicting sarcopenia through a inertial measurement unit (IMU)-based physical performance measurement data of female elderly. Patients and Methods Seventy-eight female subjects from an elderly population (aged: 78.8±5.7 years) volunteered to participate in this study. To evaluate the physical performance of the elderly, the experiment conducted timed-up-and-go test (TUG) and 6-minute walk test (6mWT) with worn a single IMU. Based on literature review, 132 features were extracted from collected data. Feature selection was performed through the Kruskal–Wallis test, and features datasets were constructed according to feature selection. Three major machine learning-based classification algorithms classified the sarcopenia group in each dataset, and the performance of classification models was compared. Results As a result of comparing the classification model performance for sarcopenia prediction, the k-nearest neighborhood algorithm (kNN) classification model using 40 major features of TUG and 6mWT showed the best performance at 88%. Conclusion This study can be used as a basic research for the development of self-monitoring technology for sarcopenia.
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Affiliation(s)
- Jeong Bae Ko
- Digital Health Care R&D Department, Korea Institute of Industrial Technology, Cheonan, Chuncheongnam-do, South Korea
| | - Kwang Bok Kim
- Digital Health Care R&D Department, Korea Institute of Industrial Technology, Cheonan, Chuncheongnam-do, South Korea
| | - Young Sub Shin
- Digital Health Care R&D Department, Korea Institute of Industrial Technology, Cheonan, Chuncheongnam-do, South Korea
| | - Hun Han
- Digital Health Care R&D Department, Korea Institute of Industrial Technology, Cheonan, Chuncheongnam-do, South Korea
| | - Sang Kuy Han
- Robotics R&D Department, Korea Institute of Industrial Technology, Ansan, Gyeonggi-do, South Korea
| | - Duk Young Jung
- Seongnam Senior Experience Complex, Eulji University, Seongnam, Gyeonggi-do, South Korea
| | - Jae Soo Hong
- Digital Health Care R&D Department, Korea Institute of Industrial Technology, Cheonan, Chuncheongnam-do, South Korea
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Which functional tasks present the largest deficits for patients with total hip arthroplasty before and six months after surgery? A study of the timed up-and-go test phases. PLoS One 2021; 16:e0255037. [PMID: 34506498 PMCID: PMC8432811 DOI: 10.1371/journal.pone.0255037] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 07/08/2021] [Indexed: 01/23/2023] Open
Abstract
Six to eight months after total hip arthroplasty, patients only attain 80% of the functional level of control groups. Understanding which functional tasks are most affected could help reduce this deficit by guiding rehabilitation towards them. The timed up-and-go test bundles multiple tasks together in one test and is a good indicator of a patient's overall level of function. Previously, biomechanical analysis of its phases was used to identify specific functional deficits in pathological populations. To the best of our knowledge, this analysis has never been performed in patients who have undergone total hip arthroplasty. Seventy-one total hip arthroplasty patients performed an instrumented timed up-and-go test in a gait laboratory before and six months after surgery; fifty-two controls performed it only once. Biomechanical features were selected to analyse the test's four phases (sit-to-stand, walking, turning, turn-to-sit) and mean differences between groups were evaluated for each phase. On average, six months after surgery, patients' overall test time rose to 80% of the mean of the control group. The walking phase was revealed as the main deficiency before and after surgery (-41 ± 47% and -22 ± 32% slower, respectively). High standard deviations indicated that variability between patients was high. On average, patients showed improved results in every phase of the timed up-and-go test six months after surgery, but residual deficits in function differed between those phases. This simple test could be appropriate for quantifying patient-specific deficits in function and hence guiding and monitoring post-operative rehabilitation in clinical settings.
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Andrenacci I, Boccaccini R, Bolzoni A, Colavolpe G, Costantino C, Federico M, Ugolini A, Vannucci A. A Comparative Evaluation of Inertial Sensors for Gait and Jump Analysis. SENSORS (BASEL, SWITZERLAND) 2021; 21:5990. [PMID: 34577200 PMCID: PMC8473286 DOI: 10.3390/s21185990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 09/02/2021] [Accepted: 09/03/2021] [Indexed: 11/23/2022]
Abstract
Gait and jump anomalies are often used as indicators to identify the presence and state of disorders that involve motor symptoms. Physical tests are often performed in specialized laboratories, which offer reliable and accurate results, but require long and costly analyses performed by specialized personnel. The use of inertial sensors for gait and jump evaluation offers an easy-to-use low-cost alternative, potentially applicable by the patients themselves at home. In this paper, we compared three inertial measurement units that are available on the market by means of well-known standardized tests for the evaluation of gait and jump behavior. The aim of the study was to highlight the strengths and weaknesses of each of the tested sensors, considered in different tests, by comparing data collected on two healthy subjects. Data were processed to identify the phases of the movement and the possible inaccuracies of each sensor. The analysis showed that some of the considered inertial units could be reliably used to identify the gait and jump phases and could be employed to detect anomalies, potentially suggesting the presence of disorders.
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Affiliation(s)
- Isaia Andrenacci
- Department of Engineering and Architecture (DEA), University of Parma, 43124 Parma, Italy; (I.A.); (R.B.); (A.B.); (M.F.); (A.U.); (A.V.)
| | - Riccardo Boccaccini
- Department of Engineering and Architecture (DEA), University of Parma, 43124 Parma, Italy; (I.A.); (R.B.); (A.B.); (M.F.); (A.U.); (A.V.)
| | - Alice Bolzoni
- Department of Engineering and Architecture (DEA), University of Parma, 43124 Parma, Italy; (I.A.); (R.B.); (A.B.); (M.F.); (A.U.); (A.V.)
| | - Giulio Colavolpe
- Department of Engineering and Architecture (DEA), University of Parma, 43124 Parma, Italy; (I.A.); (R.B.); (A.B.); (M.F.); (A.U.); (A.V.)
| | - Cosimo Costantino
- Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy;
| | - Michelangelo Federico
- Department of Engineering and Architecture (DEA), University of Parma, 43124 Parma, Italy; (I.A.); (R.B.); (A.B.); (M.F.); (A.U.); (A.V.)
| | - Alessandro Ugolini
- Department of Engineering and Architecture (DEA), University of Parma, 43124 Parma, Italy; (I.A.); (R.B.); (A.B.); (M.F.); (A.U.); (A.V.)
| | - Armando Vannucci
- Department of Engineering and Architecture (DEA), University of Parma, 43124 Parma, Italy; (I.A.); (R.B.); (A.B.); (M.F.); (A.U.); (A.V.)
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Effects of using assistive devices on the components of the modified instrumented timed up and go test in healthy subjects. Heliyon 2021; 7:e06940. [PMID: 34007923 PMCID: PMC8111581 DOI: 10.1016/j.heliyon.2021.e06940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 04/13/2021] [Accepted: 04/23/2021] [Indexed: 11/23/2022] Open
Abstract
Introduction Evaluation of the changes in gait spatiotemporal parameters and functional mobility with using assistive devices (ADs) would provide useful information and mutual assistance when prescribing such ambulatory devices. This study aimed to investigate the spatiotemporal gait and functional mobility parameters in healthy adults when walking using different ADs. Methods A group of healthy subjects participated in the study. The instrumented modified Timed Up and Go test (iTUG) was used to investigate the impact of different types of ADs on spatiotemporal and functional mobility parameters. Results Subjects showed a significant difference in the gait task performance (P = .001) in stride velocity, stride length, and cadence when walking with and without ADs. A significant difference was also found in the performance of the turn-to-sit task (P = .001) in both velocity and duration when walking with and without ADs. The time to complete sit-to-stand was significantly slower when using a walker (98.3 ± 22.3°/sec, P = .004) and a cane (78.2 ± 21.9°/sec, P = .004) compared to walking without an AD (78.2 ± 21.8°/sec). No significant difference was found between walking with a cane group versus walking with a four-wheeled walker group (P = .94). Conclusion ADs altered gait and functional mobility parameters differently in healthy subjects. Using a four-wheeled walker showed a tendency to increase stride velocity, cadence, stride length, and slow sit-to-stand velocity compared to using a cane. The findings highlight using more caution clinically when prescribing ADs and providing gait training.
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Hansen C, Beckbauer M, Romijnders R, Warmerdam E, Welzel J, Geritz J, Emmert K, Maetzler W. Reliability of IMU-Derived Static Balance Parameters in Neurological Diseases. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18073644. [PMID: 33807432 PMCID: PMC8037984 DOI: 10.3390/ijerph18073644] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 01/03/2023]
Abstract
Static balance is a commonly used health measure in clinical practice. Usually, static balance parameters are assessed via force plates or, more recently, with inertial measurement units (IMUs). Multiple parameters have been developed over the years to compare patient groups and understand changes over time. However, the day-to-day variability of these parameters using IMUs has not yet been tested in a neurogeriatric cohort. The aim of the study was to examine day-to-day variability of static balance parameters of five experimental conditions in a cohort of neurogeriatric patients using data extracted from a lower back-worn IMU. A group of 41 neurogeriatric participants (age: 78 ± 5 years) underwent static balance assessment on two occasions 12-24 h apart. Participants performed a side-by-side stance, a semi-tandem stance, a tandem stance on hard ground with eyes open, and a semi-tandem assessment on a soft surface with eyes open and closed for 30 s each. The intra-class correlation coefficient (two-way random, average of the k raters' measurements, ICC2, k) and minimal detectable change at a 95% confidence level (MDC95%) were calculated for the sway area, velocity, acceleration, jerk, and frequency. Velocity, acceleration, and jerk were calculated in both anterior-posterior (AP) and medio-lateral (ML) directions. Nine to 41 participants could successfully perform the respective balance tasks. Considering all conditions, acceleration-related parameters in the AP and ML directions gave the highest ICC results. The MDC95% values for all parameters ranged from 39% to 220%, with frequency being the most consistent with values of 39-57%, followed by acceleration in the ML (43-55%) and AP direction (54-77%). The present results show moderate to poor ICC and MDC values for IMU-based static balance assessment in neurogeriatric patients. This suggests a limited reliability of these tasks and parameters, which should induce a careful selection of potential clinically relevant parameters.
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Affiliation(s)
- Clint Hansen
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
- Correspondence:
| | - Maximilian Beckbauer
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
| | - Robbin Romijnders
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
- Digital Signal Processing and System Theory, Institute of Electrical and Information Engineering, Kiel University, Kaiserstrasse 2, 24143 Kiel, Germany
| | - Elke Warmerdam
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
- Digital Signal Processing and System Theory, Institute of Electrical and Information Engineering, Kiel University, Kaiserstrasse 2, 24143 Kiel, Germany
| | - Julius Welzel
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
| | - Johanna Geritz
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
| | - Kirsten Emmert
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
| | - Walter Maetzler
- Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Strasse 3, Haus D, 24105 Kiel, Germany; (M.B.); (R.R.); (E.W.); (J.W.); (J.G.); (K.E.); (W.M.)
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Automatic Functional Shoulder Task Identification and Sub-task Segmentation Using Wearable Inertial Measurement Units for Frozen Shoulder Assessment. SENSORS 2020; 21:s21010106. [PMID: 33375341 PMCID: PMC7795360 DOI: 10.3390/s21010106] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 12/22/2020] [Accepted: 12/22/2020] [Indexed: 11/26/2022]
Abstract
Advanced sensor technologies have been applied to support frozen shoulder assessment. Sensor-based assessment tools provide objective, continuous and quantitative information for evaluation and diagnosis. However, the current tools for assessment of functional shoulder tasks mainly rely on manual operation. It may cause several technical issues to the reliability and usability of the assessment tool, including manual bias during the recording and additional efforts for data labeling. To tackle these issues, this pilot study aims to propose an automatic functional shoulder task identification and sub-task segmentation system using inertial measurement units to provide reliable shoulder task labeling and sub-task information for clinical professionals. The proposed method combines machine learning models and rule-based modification to identify shoulder tasks and segment sub-tasks accurately. A hierarchical design is applied to enhance the efficiency and performance of the proposed approach. Nine healthy subjects and nine frozen shoulder patients are invited to perform five common shoulder tasks in the lab-based and clinical environments, respectively. The experimental results show that the proposed method can achieve 87.11% F-score for shoulder task identification, and 83.23% F-score and 427 mean absolute time errors (milliseconds) for sub-task segmentation. The proposed approach demonstrates the feasibility of the proposed method to support reliable evaluation for clinical assessment.
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Addabbo T, Fort A, Intravaia M, Mugnaini M, Tani M, Vignoli V, De Muro S, Tesei M. Working Principle and Performance of a Scalable Gravimetric System for the Monitoring of Access to Public Places. SENSORS 2020; 20:s20247225. [PMID: 33348623 PMCID: PMC7767313 DOI: 10.3390/s20247225] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 12/11/2020] [Accepted: 12/15/2020] [Indexed: 11/16/2022]
Abstract
Here, we propose a novel application of a low-cost robust gravimetric system for public place access monitoring purposes. The proposed solution is intended to be exploited in a multi-sensor scenario, where heterogeneous information, coming from different sources (e.g., metal detectors and surveillance cameras), are collected in a central data fusion unit to obtain a more detailed and accurate evaluation of notable events. Specifically, the word “notable” refers essentially to two event categories: the first category is represented by irregular events, corresponding typically to multiple people passing together through a security gate; the second category includes some event subsets, whose notification can be interesting for assistance provision (in the case of people with disabilities), or for statistical analysis. The employed gravimetric sensor, compared to other devices existing in the literature, exhibits a simple scalable robust structure, made up of an array of rigid steel plates, each laid on four load cells. We developed a tailored hardware and software to individually acquire the load cell signals, and to post-process the data to formulate a classification of the notable events. The results are encouraging, showing a remarkable detectability of irregularities (95.3% of all the test cases) and a satisfactory identification of the other event types.
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Affiliation(s)
- Tommaso Addabbo
- Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy; (T.A.); (A.F.); (M.M.); (M.T.); (V.V.)
| | - Ada Fort
- Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy; (T.A.); (A.F.); (M.M.); (M.T.); (V.V.)
| | - Matteo Intravaia
- Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy; (T.A.); (A.F.); (M.M.); (M.T.); (V.V.)
- Correspondence:
| | - Marco Mugnaini
- Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy; (T.A.); (A.F.); (M.M.); (M.T.); (V.V.)
| | - Marco Tani
- Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy; (T.A.); (A.F.); (M.M.); (M.T.); (V.V.)
| | - Valerio Vignoli
- Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, 53100 Siena, Italy; (T.A.); (A.F.); (M.M.); (M.T.); (V.V.)
| | - Stefano De Muro
- Rete Ferroviaria Italiana S.p.A. Direzione Protezione Aziendale, Piazza della Croce Rossa 1, 00161 Roma, Italy; (S.D.M.); (M.T.)
| | - Marco Tesei
- Rete Ferroviaria Italiana S.p.A. Direzione Protezione Aziendale, Piazza della Croce Rossa 1, 00161 Roma, Italy; (S.D.M.); (M.T.)
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Picardi M, Redaelli V, Antoniotti P, Pintavalle G, Aristidou E, Sterpi I, Meloni M, Corbo M, Caronni A. Turning and sit-to-walk measures from the instrumented Timed Up and Go test return valid and responsive measures of dynamic balance in Parkinson's disease. Clin Biomech (Bristol, Avon) 2020; 80:105177. [PMID: 32979787 DOI: 10.1016/j.clinbiomech.2020.105177] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 06/28/2020] [Accepted: 09/09/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Balance impairment is a hallmark of Parkinson's disease with dramatic effects for patients (e.g. falls). Its assessment is thus of paramount importance. The aim of this work is to assess which measures from the instrumented Timed Up and Go test (recorded with inertial sensors) are valid balance measures in Parkinson's disease and evaluate their responsiveness to rehabilitation. METHODS The Mini-BESTest (a criterion-standard balance measure) and the instrumented Timed Up and Go test (with inertial sensors secured to the trunk) were administered to 20 Parkinson's disease patients before and after inpatient rehabilitation (median [IQR]; 76.5 [8.25] years; 5 females; Hoehn and Yahr stage: 2.5 [0.5]). 81 parameters from the instrumented Timed Up and Go test were evaluated. Multiple factor analysis (a variant of principal component analysis for repeated measurements) and effect sizes were used to assess validity and responsiveness, respectively. FINDINGS Only the first component of the multiple factor analysis correlated with the Mini-BESTest, and 21 measures from the instrumented Timed Up and Go test had large loadings on this component. However, only three of these 21 measures also directly correlated with the Mini-BESTest (trunk angular velocities from sit-to-walk and turning; r = 0.46 to 0.50, P = 0.021 to 0.038). Sit-to-walk angular velocity showed greater responsiveness than the Mini-BESTest, while turning showed slightly less. INTERPRETATION Angular velocities from the turning and sit-to-walk phases of the Timed Up and Go test are valid balance measures in Parkinson's disease and are also responsive to rehabilitation.
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Affiliation(s)
- Michela Picardi
- Department of Neurorehabilitation Sciences, Casa di Cura del Policlinico, Via Dezza 48, Milano 20144, Italy
| | - Valentina Redaelli
- Department of Neurorehabilitation Sciences, Casa di Cura del Policlinico, Via Dezza 48, Milano 20144, Italy
| | - Paola Antoniotti
- Department of Neurorehabilitation Sciences, Casa di Cura del Policlinico, Via Dezza 48, Milano 20144, Italy
| | - Giuseppe Pintavalle
- Department of Neurorehabilitation Sciences, Casa di Cura del Policlinico, Via Dezza 48, Milano 20144, Italy
| | - Evdoxia Aristidou
- Department of Neurorehabilitation Sciences, Casa di Cura del Policlinico, Via Dezza 48, Milano 20144, Italy
| | - Irma Sterpi
- Department of Neurorehabilitation Sciences, Casa di Cura del Policlinico, Via Dezza 48, Milano 20144, Italy
| | - Mario Meloni
- IRCCS Fondazione Don Carlo Gnocchi Onlus, via Alfonso Capecelatro 66, Milano 20148, Italy
| | - Massimo Corbo
- Department of Neurorehabilitation Sciences, Casa di Cura del Policlinico, Via Dezza 48, Milano 20144, Italy
| | - Antonio Caronni
- IRCCS Fondazione Don Carlo Gnocchi Onlus, via Alfonso Capecelatro 66, Milano 20148, Italy.
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Shah VV, Curtze C, Mancini M, Carlson-Kuhta P, Nutt JG, Gomez CM, El-Gohary M, Horak FB, McNames J. Inertial Sensor Algorithms to Characterize Turning in Neurological Patients With Turn Hesitations. IEEE Trans Biomed Eng 2020; 68:2615-2625. [PMID: 33180719 DOI: 10.1109/tbme.2020.3037820] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND One difficulty in turning algorithm design for inertial sensors is detecting two discrete turns in the same direction, close in time. A second difficulty is under-estimation of turn angle due to short-duration hesitations by people with neurological disorders. We aimed to validate and determine the generalizability of a: I. Discrete Turn Algorithm for variable and sequential turns close in time and II: Merged Turn Algorithm for a single turn angle in the presence of hesitations. METHODS We validated the Discrete Turn Algorithm with motion capture in healthy controls (HC, n = 10) performing a spectrum of turn angles. Subsequently, the generalizability of the Discrete Turn Algorithm and associated, Merged Turn Algorithm were tested in people with Parkinson's disease (PD, n = 124), spinocerebellar ataxia (SCA, n = 51), and HC (n = 125). RESULTS The Discrete Turn Algorithm shows improved agreement with optical motion capture and with known turn angles, compared to our previous algorithm by El-Gohary et al. The Merged Turn algorithm that merges consecutive turns in the same direction with short hesitations resulted in turn angle estimates closer to a fixed 180-degree turn angle in the PD, SCA, and HC subjects compared to our previous turn algorithm. Additional metrics were proposed to capture turn hesitations in PD and SCA. CONCLUSION The Discrete Turn Algorithm may be particularly useful to characterize turns when the turn angle is unknown, i.e., during free-living conditions. The Merged Turn algorithm is recommended for clinical tasks in which the single-turn angle is known, especially for patients who hesitate while turning.
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Ponciano V, Pires IM, Ribeiro FR, Spinsante S. Sensors are Capable to Help in the Measurement of the Results of the Timed-Up and Go Test? A Systematic Review. J Med Syst 2020; 44:199. [PMID: 33070247 DOI: 10.1007/s10916-020-01666-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Accepted: 10/12/2020] [Indexed: 11/24/2022]
Abstract
The analysis of movements used in physiotherapy areas related to the elderly is becoming increasingly important due to factors such as the increase in the average life expectancy and the rate of elderly people over the whole population. In this systematic review, we try to determine how the inertial sensors embedded in mobile devices are exploited for the measurement of the different parameters involved in the Timed-Up and Go test. The results show the mobile devices equipped with onboard motion sensors can be exploited for these types of studies: the most commonly used sensors are the magnetometer, accelerometer and gyroscope available in consumer off-the-shelf smartphones. Other features typically used to evaluate the Timed-Up and Go test are the time duration, the angular velocity and the number of steps, allowing for the recognition of some diseases as well as the measurement of the subject's performance during the test execution.
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Affiliation(s)
- Vasco Ponciano
- R&D Unit in Digital Services, Applications and Content, Polytechnic Institute of Castelo Branco, Castelo Branco, Portugal. .,Altranportugal, Lisbon, Portugal.
| | - Ivan Miguel Pires
- Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal.,Computer Science Department, Polytechnic Institute of Viseu, Viseu, Portugal.,UICISA:E Research Centre, School of Health, Polytechnic Institute of Viseu, Viseu, Portugal
| | - Fernando Reinaldo Ribeiro
- R&D Unit in Digital Services, Applications and Content, Polytechnic Institute of Castelo Branco, Castelo Branco, Portugal
| | - Susanna Spinsante
- Department of Information Engineering, Marche Polytechnic University, Ancona, Italy
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Fujita K, Iijima H, Eguchi R, Kuroiwa T, Sasaki T, Yokoyama Y, Koyama T, Nimura A, Kato R, Okawa A, Takahashi M. Gait analysis of patients with distal radius fracture by using a novel laser Timed Up-and-Go system. Gait Posture 2020; 80:223-227. [PMID: 32540778 DOI: 10.1016/j.gaitpost.2020.06.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Revised: 05/14/2020] [Accepted: 06/04/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND Postmenopausal women are at risk of fall and fracture with the physical decline. Distal radius fracture (DRF) is considered as the primary fragility fracture, and women with this fracture showed poor results in the usual Timed Up-and-Go (TUG) test, indicating a decline in balance and physical ability. The detailed physical characteristics of female DRF patients have not been extensively examined. RESEARCH QUESTION Is the novel laser TUG system able to detect and analyze the detailed gait characteristics in patients with DRF whose physical ability has tended to decline? METHODS In this cross-sectional case control study, the gait characteristics of 32 female patients with DRF who had undergone surgery were evaluated at 2 weeks postoperatively with a laser TUG system to analyze the detailed leg motion during normal TUG test. Forty-three age- and sex-matched non-fractured women were evaluated by the laser TUG system as controls. Lifestyle and present illness were corrected at the time of TUG measurement. Detailed data during laser TUG in both groups were compared statistically, and odds ratio and thread shod of the fracture was elucidated through a logistic regression analysis. RESULTS DRF patients showed slower speed and had to do more steps to complete the TUG test. Furthermore, asymmetric trajectory and significantly further distance from the marker were observed. Thirteen steps to complete the TUG test was the thread shod of DRF. SIGNIFICANCE Detailed gait characteristics of patients with DRF were detected by the laser TUG system. The gait decline and abnormality could be one of the reasons of consecutive fragility fracture. To prevent secondary fragility fractures, this system can be useful for screening.
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Affiliation(s)
- Koji Fujita
- Department of Orthopaedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.
| | - Hirotaka Iijima
- Department of System Design and Engineering, Faculty of Science and Technology, Keio University, Kanagawa, Japan
| | - Ryo Eguchi
- Department of System Design and Engineering, Faculty of Science and Technology, Keio University, Kanagawa, Japan
| | - Tomoyuki Kuroiwa
- Department of Orthopaedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Toru Sasaki
- Department of Orthopaedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yukihiro Yokoyama
- Department of Orthopaedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Takafumi Koyama
- Department of Orthopaedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Akimoto Nimura
- Department of Functional Joint Anatomy, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | | | - Atsushi Okawa
- Department of Orthopaedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Masaki Takahashi
- Department of System Design and Engineering, Faculty of Science and Technology, Keio University, Kanagawa, Japan
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Sport Biomechanics Applications Using Inertial, Force, and EMG Sensors: A Literature Overview. Appl Bionics Biomech 2020; 2020:2041549. [PMID: 32676126 PMCID: PMC7330631 DOI: 10.1155/2020/2041549] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Revised: 05/26/2020] [Accepted: 06/05/2020] [Indexed: 11/17/2022] Open
Abstract
In the last few decades, a number of technological developments have advanced the spread of wearable sensors for the assessment of human motion. These sensors have been also developed to assess athletes' performance, providing useful guidelines for coaching, as well as for injury prevention. The data from these sensors provides key performance outcomes as well as more detailed kinematic, kinetic, and electromyographic data that provides insight into how the performance was obtained. From this perspective, inertial sensors, force sensors, and electromyography appear to be the most appropriate wearable sensors to use. Several studies were conducted to verify the feasibility of using wearable sensors for sport applications by using both commercially available and customized sensors. The present study seeks to provide an overview of sport biomechanics applications found from recent literature using wearable sensors, highlighting some information related to the used sensors and analysis methods. From the literature review results, it appears that inertial sensors are the most widespread sensors for assessing athletes' performance; however, there still exist applications for force sensors and electromyography in this context. The main sport assessed in the studies was running, even though the range of sports examined was quite high. The provided overview can be useful for researchers, athletes, and coaches to understand the technologies currently available for sport performance assessment.
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Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults. SENSORS 2020; 20:s20123481. [PMID: 32575650 PMCID: PMC7349529 DOI: 10.3390/s20123481] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 06/15/2020] [Accepted: 06/17/2020] [Indexed: 02/05/2023]
Abstract
Due to the increasing age of the European population, there is a growing interest in performing research that will aid in the timely and unobtrusive detection of emerging diseases. For such tasks, mobile devices have several sensors, facilitating the acquisition of diverse data. This study focuses on the analysis of the data collected from the mobile devices sensors and a pressure sensor connected to a Bitalino device for the measurement of the Timed-Up and Go test. The data acquisition was performed within different environments from multiple individuals with distinct types of diseases. Then this data was analyzed to estimate the various parameters of the Timed-Up and Go test. Firstly, the pressure sensor is used to extract the reaction and total test time. Secondly, the magnetometer sensors are used to identify the total test time and different parameters related to turning around. Finally, the accelerometer sensor is used to extract the reaction time, total test time, duration of turning around, going time, return time, and many other derived metrics. Our experiments showed that these parameters could be automatically and reliably detected with a mobile device. Moreover, we identified that the time to perform the Timed-Up and Go test increases with age and the presence of diseases related to locomotion.
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Abstract
The number of older adults is increasing worldwide, and it is expected that by 2050 over 2 billion individuals will be more than 60 years old. Older adults are exposed to numerous pathological problems such as Parkinson’s disease, amyotrophic lateral sclerosis, post-stroke, and orthopedic disturbances. Several physiotherapy methods that involve measurement of movements, such as the Timed-Up and Go test, can be done to support efficient and effective evaluation of pathological symptoms and promotion of health and well-being. In this systematic review, the authors aim to determine how the inertial sensors embedded in mobile devices are employed for the measurement of the different parameters involved in the Timed-Up and Go test. The main contribution of this paper consists of the identification of the different studies that utilize the sensors available in mobile devices for the measurement of the results of the Timed-Up and Go test. The results show that mobile devices embedded motion sensors can be used for these types of studies and the most commonly used sensors are the magnetometer, accelerometer, and gyroscope available in off-the-shelf smartphones. The features analyzed in this paper are categorized as quantitative, quantitative + statistic, dynamic balance, gait properties, state transitions, and raw statistics. These features utilize the accelerometer and gyroscope sensors and facilitate recognition of daily activities, accidents such as falling, some diseases, as well as the measurement of the subject’s performance during the test execution.
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Montero-Odasso M, Almeida QJ, Bherer L, Burhan AM, Camicioli R, Doyon J, Fraser S, Muir-Hunter S, Li KZH, Liu-Ambrose T, McIlroy W, Middleton L, Morais JA, Sakurai R, Speechley M, Vasudev A, Beauchet O, Hausdorff JM, Rosano C, Studenski S, Verghese J. Consensus on Shared Measures of Mobility and Cognition: From the Canadian Consortium on Neurodegeneration in Aging (CCNA). J Gerontol A Biol Sci Med Sci 2020; 74:897-909. [PMID: 30101279 PMCID: PMC6521916 DOI: 10.1093/gerona/gly148] [Citation(s) in RCA: 110] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Indexed: 02/02/2023] Open
Abstract
Background A new paradigm is emerging in which mobility and cognitive impairments, previously studied, diagnosed, and managed separately in older adults, are in fact regulated by shared brain resources. Deterioration in these shared brain mechanisms by normal aging and neurodegeneration increases the risk of developing dementia, falls, and fractures. This new paradigm requires an integrated approach to measuring both domains. We aim to identify a complementary battery of existing tests of mobility and cognition in community-dwelling older adults that enable assessment of motor-cognitive interactions. Methods Experts on mobility and cognition in aging participated in a semistructured consensus based on the Delphi process. After performing a scoping review to select candidate tests, multiple rounds of consultations provided structured feedback on tests that captured shared characteristics of mobility and cognition. These tests needed to be sensitive to changes in both mobility and cognition, applicable across research studies and clinics, sensitive to interventions, feasible to perform in older adults, been previously validated, and have minimal ceiling/floor effects. Results From 17 tests appraised, 10 tests fulfilled prespecified criteria and were selected as part of the “Core-battery” of tests. The expert panel also recommended a “Minimum-battery” of tests that included gait speed, dual-task gait speed, the Montreal Cognitive Assessment and Trail Making Test A&B. Conclusions A standardized assessment battery that captures shared characteristics of mobility and cognition seen in aging and neurodegeneration may increase comparability across research studies, detection of subtle or common reversible factors, and accelerate research progress in dementia, falls, and aging-related disabilities.
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Affiliation(s)
- Manuel Montero-Odasso
- Department of Medicine, Division of Geriatric Medicine, University of Western Ontario, London, Canada
- Department of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Canada
- Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, London, Ontario, Canada
- Address correspondence to: Manuel Montero-Odasso MD, PhD, AGSF, FRCPC, FGSA, Gait and Brain Lab, Parkwood Institute, University of Western Ontario and Lawson Health Research Institute, 550 Wellington Road, London, Ontario N6C 0A7, Canada. E-mail:
| | - Quincy J Almeida
- Department of Kinesiology and Physical Education, Sun Life Financial Movement Disorders Research Centre, Wilfrid Laurier University, Waterloo, Ontario, Canada
| | - Louis Bherer
- Department of Psychology and PERFORM Centre, Concordia University, Montréal, Quebec, Canada
- Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, Quebec, Canada
- Department of Medicine, University of Montreal, Quebec, Canada
- Montreal Heart Institute, Research Centre, Quebec, Canada
| | - Amer M Burhan
- Department of Psychiatry, Geriatric Psychiatry, Schulich School of Medicine, University of Western Ontario, London, Canada
- Lawson Health Research Institute, London, Ontario, Canada
| | - Richard Camicioli
- Department of Medicine, Geriatric and Cognitive Neurology, University of Alberta, Edmonton, Canada
| | - Julien Doyon
- Functional Neuroimaging Unit, University of Montreal, Quebec, Canada
| | - Sarah Fraser
- Interdisciplinary School of Health Sciences, Faculty of Health Sciences, University of Ottawa, Ontario, Canada
| | - Susan Muir-Hunter
- Department of Medicine, Division of Geriatric Medicine, University of Western Ontario, London, Canada
- Faculty of Health Sciences, School of Physical Therapy, University of Western Ontario, London, Canada
| | - Karen Z H Li
- Department of Psychology and PERFORM Centre, Concordia University, Montréal, Quebec, Canada
| | - Teresa Liu-Ambrose
- Department of Physical Therapy, Centre for Hip Health and Mobility, University of British Columbia, Canada
- Djavad Mowafaghian Centre for Brain Health, Vancouver Coastal Research Institute, University of British Columbia, Canada
| | - William McIlroy
- Division of Neurology and Department of Medicine, University of Toronto, Ontario, Canada
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Ontario, Canada
- Department of Kinesiology, University of Waterloo, Ontario, Canada
| | - Laura Middleton
- Department of Kinesiology, University of Waterloo, Ontario, Canada
| | - José A Morais
- Department of Medicine, Division of Geriatrics and Centre of Excellence in Aging and Chronic Disease, McGill University, Montréal, Quebec, Canada
| | - Ryota Sakurai
- Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, London, Ontario, Canada
| | - Mark Speechley
- Department of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Canada
| | - Akshya Vasudev
- Department of Psychiatry, Geriatric Psychiatry, Schulich School of Medicine, University of Western Ontario, London, Canada
- Department of Medicine, Division of Clinical Pharmacology, University of Western Ontario, London, Canada
| | - Olivier Beauchet
- Department of Medicine, Division of Geriatric Medicine, McGill University, Montréal, Quebec, Canada
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Quebec, Canada
- RUIS McGill Centre of Excellence on Aging and Chronic Disease – CEViMaC, Montréal, Quebec, Canada
| | - Jeffrey M Hausdorff
- Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Israel
- Department of Physical Therapy, Sackler Faculty of Medicine, and Sagol School of Neuroscience, Tel Aviv University, Israel
- Rush Alzheimer’s Disease Center and Department of Orthopedic Surgery, Rush University Medical Center, Chicago, Illinois
| | - Caterina Rosano
- Department of Epidemiology, University of Pittsburgh, Pennsylvania
| | - Stephanie Studenski
- Division of Geriatric Medicine, School of Medicine, University of Pittsburgh, Pennsylvania
| | - Joe Verghese
- Department of Medicine, Albert Einstein College of Medicine, Bronx, New York
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Savoie P, Cameron JAD, Kaye ME, Scheme EJ. Automation of the Timed-Up-and-Go Test Using a Conventional Video Camera. IEEE J Biomed Health Inform 2019; 24:1196-1205. [PMID: 31403450 DOI: 10.1109/jbhi.2019.2934342] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The Timed-Up-and-Go (TUG) test is a simple clinical tool commonly used to quickly assess the mobility of patients. Researchers have endeavored to automate the test using sensors or motion tracking systems to improve its accuracy and to extract more resolved information about its sub-phases. While some approaches have shown promise, they often require the donning of sensors or the use of specialized hardware, such as the now discontinued Microsoft Kinect, which combines video information with depth sensors (RGBD). In this work, we leverage recent advances in computer vision to automate the TUG test using a regular RGB video camera without the need for custom hardware or additional depth sensors. Thirty healthy participants were recorded using a Kinect V2 and a standard video feed while performing multiple trials of 3 and 1.5 meter versions of the TUG test. A Mask Regional Convolutional Neural Net (R-CNN) algorithm and a Deep Multitask Architecture for Human Sensing (DMHS) were then used together to extract global 3D poses of the participants. The timing of transitions between the six key movement phases of the TUG test were then extracted using heuristic features extracted from the time series of these 3D poses. The proposed video-based vTUG system yielded the same error as the standard Kinect-based system for all six key transitions points, and average errors of less than 0.15 seconds from a multi-observer hand labeled ground truth. This work describes a novel method of video-based automation of the TUG test using a single standard camera, removing the need for specialized equipment and facilitating the extraction of additional meaningful information for clinical use.
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Janssen S, Heijs JJA, van der Meijs W, Nonnekes J, Bittner M, Dorresteijn LDA, Bloem BR, van Wezel RJA, Heida T. Validation of the Auditory Stroop Task to increase cognitive load in walking tasks in healthy elderly and persons with Parkinson's disease. PLoS One 2019; 14:e0220735. [PMID: 31386695 PMCID: PMC6684087 DOI: 10.1371/journal.pone.0220735] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Accepted: 07/21/2019] [Indexed: 11/18/2022] Open
Abstract
Background The development of treatments for freezing of gait (FOG) in Parkinson’s disease (PD) requires experimental study set-ups in which FOG is likely to occur, and is amenable to therapeutic interventions. We explore whether the ‘Auditory Stroop Task’ (AST) can be used to increase cognitive load (and thereby elicit FOG), simultaneously with visual cues (as a therapeutic intervention for FOG). We additionally examined how these two contrasting effects might interact in affecting gait and FOG parameters. Objectives We investigated whether: (1) the ‘Auditory Stroop Task’ (AST) influences gait in healthy elderly and persons with PD who experience FOG, and increases the frequency of FOG events among PD patients; (2) the AST and visual cues interact; and (3) different versions of the AST exert different cognitive loads. Methods In ‘Experiment 1’, 19 healthy elderly subjects performed a walking task while performing a high and low load version of the AST. Walking with a random numbers task, and walking without cognitive load served as control conditions. In ‘Experiment 2’, 20 PD patients with FOG and 18 healthy controls performed a walking task with the AST, and no additional cognitive load as control condition. Both experiments were performed with and without visual cues. Velocity, cadence, stride length, and stride time were measured in all subjects. FOG severity was measured in patients. Results Compared to the control conditions, the AST negatively affected all gait parameters in both patients and controls. The AST did not increase the occurrence of FOG in patients. Visual cues reduced the decline in stride length induced by cognitive load in both groups. Both versions of the AST exerted similar effects on gait parameters in controls. Conclusions The AST is well-suited to simulate the effects of cognitive load on gait parameters, but not FOG severity, in gait experiments in persons with PD and FOG.
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Affiliation(s)
- S. Janssen
- Biomedical Signals and Systems Group, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
- * E-mail:
| | - J. J. A. Heijs
- Biomedical Signals and Systems Group, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
| | - W. van der Meijs
- Department of Biophysics, Donders Institute of Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - J. Nonnekes
- Department of Rehabilitation, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - M. Bittner
- Biomedical Signals and Systems Group, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
| | | | - B. R. Bloem
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - R. J. A. van Wezel
- Biomedical Signals and Systems Group, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
- Department of Biophysics, Donders Institute of Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - T. Heida
- Biomedical Signals and Systems Group, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
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Instrumented Crutch Tip for Monitoring Force and Crutch Pitch Angle. SENSORS 2019; 19:s19132944. [PMID: 31277380 PMCID: PMC6650966 DOI: 10.3390/s19132944] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 06/25/2019] [Accepted: 06/30/2019] [Indexed: 02/07/2023]
Abstract
In rehabilitation procedures related to the lower limbs, gait monitoring is an important source of information for the therapist. However, many of the approaches proposed in the literature require the use of uncomfortable and invasive devices. In this work, an instrumented tip is developed and detailed, which can be connected to any crutch. The instrumented tip provides objective data of the crutch motion, which, combined with patient movement data, might be used to monitor the daily activities or assess the recovery status of the patient. For that purpose, the tip integrates a two-axis inclinometer, a tri-axial gyroscope, and a force sensor to measure the force exerted on the crutch. In addition, a novel algorithm to estimate the pitch angle of the crutch is developed. The proposed approach is tested experimentally, obtaining acceptable accuracies and demonstrating the validity of the proposed lightweight, portable solution for gait monitoring.
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Use of a Single Wireless IMU for the Segmentation and Automatic Analysis of Activities Performed in the 3-m Timed Up & Go Test. SENSORS 2019; 19:s19071647. [PMID: 30959897 PMCID: PMC6480218 DOI: 10.3390/s19071647] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 03/12/2019] [Accepted: 03/19/2019] [Indexed: 12/15/2022]
Abstract
Falls represent a major public health problem in the elderly population. The Timed Up & Go test (TU & Go) is the most used tool to measure this risk of falling, which offers a unique parameter in seconds that represents the dynamic balance. However, it is not determined in which activity the subject presents greater difficulties. For this, a feature-based segmentation method using a single wireless Inertial Measurement Unit (IMU) is proposed in order to analyze data of the inertial sensors to provide a complete report on risks of falls. Twenty-five young subjects and 12 older adults were measured to validate the method proposed with an IMU in the back and with video recording. The measurement system showed similar data compared to the conventional test video recorded, with a Pearson correlation coefficient of 0.9884 and a mean error of 0.17 ± 0.13 s for young subjects, as well as a correlation coefficient of 0.9878 and a mean error of 0.2 ± 0.22 s for older adults. Our methodology allows for identifying all the TU & Go sub–tasks with a single IMU automatically providing information about variables such as: duration of sub–tasks, standing and sitting accelerations, rotation velocity of turning, number of steps during walking and turns, and the inclination degrees of the trunk during standing and sitting.
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Kuo FC. Acceleration Pattern and Neuromuscular Response of the Spine and Ankle During the Limits-of-Stability Test. J Strength Cond Res 2019; 34:857-865. [PMID: 30844993 DOI: 10.1519/jsc.0000000000003062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Kuo, FC. Acceleration pattern and neuromuscular response of the spine and ankle during the limits-of-stability test. J Strength Cond Res 34(3): 857-865, 2020-This study aimed to explore the acceleration amplitude, frequency, and electromyography (EMG) activity at the spine, pelvis, and lower extremities under various platform-stability settings. Thirty two young adults (16 men and 16 women) were recruited from a university in Taiwan. A balance system for limits-of-stability testing was used with 2 platform stability settings (i.e., level 4 and static). An inertial motion system and a telemetry EMG system were used to record kinematic and EMG data. Consequently, compared with the level 4 setting, the static-level setting required greater thoracic lateral flexion, pelvic course, and pelvic pitch; greater acceleration amplitudes of the spine, pelvis, and thigh; and greater acceleration frequencies at the shin and ankle. Participants exhibited a significant increase in knee flexion, ankle abduction, foot acceleration, and activity of the rectus femoris and tibialis anterior muscles when the platform stability was decreased. In addition, higher median frequencies of the spine and pelvis and larger amplitudes of the foot were observed under the level 4 setting. The men exhibited a larger range of motion in lumbar joint and thoracic rotation than did the women. To maintain stability, subjects must readjust their head, spine, and ankle movement amplitudes and frequencies depending on the platform stability. The study findings suggest the use of static platform settings for spine control facilitation and unstable platform settings for proprioception and muscle strengthening of lower extremity.
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Affiliation(s)
- Fang-Chuan Kuo
- Department of Physical Therapy, Hungkuang University, Taichung, Taiwan
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Cimolin V, Cau N, Malchiodi Albedi G, Aspesi V, Merenda V, Galli M, Capodaglio P. Do wearable sensors add meaningful information to the Timed Up and Go test? A study on obese women. J Electromyogr Kinesiol 2018; 44:78-85. [PMID: 30551006 DOI: 10.1016/j.jelekin.2018.12.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Revised: 11/23/2018] [Accepted: 12/04/2018] [Indexed: 02/06/2023] Open
Abstract
The purpose of this study was to validate Time Up and Go test (TUG) as measured by a single Inertial Measurement Unit (IMU) placed on the lower back to that measured by a stopwatch in obese and normal weight women; in addition, the comparison of the performance of TUG test between obese and healthy women using the instrumented TUG (iTUG). Forty-four severely obese women and 14 age-matched healthy women were assessed simultaneously by IMU and stopwatch. The comparison between manual and instrumented assessment of total time duration showed no significant differences both in the healthy (8.32 ± 0.96 s vs. 8.52 ± 0.97 s, p > 0.05) and in the obese group (9.99 ± 2.28 s vs. 9.81 ± 2.52 s; p > 0.05). The comparison between obese and healthy group exhibited significant differences in terms of total time duration both during manual and iTUG, which is longer in obese women than normal weight women. The duration of the sub-phases in obese group is longer with the exception of sit-to-stand and stand-to-sit phase, with lower turning velocity both in mid- and final turning sub-phase. The results suggest that the iTUG is an objective and fast mobility test and it could add useful information to the manual TUG for clinical practice.
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Affiliation(s)
- Veronica Cimolin
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, p.za Leonardo da Vinci 32, 20133 Milan, Italy.
| | - Nicola Cau
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, p.za Leonardo da Vinci 32, 20133 Milan, Italy; Rehabilitation Unit and Research Lab in Biomechanics and Rehabilitation, S Giuseppe Hospital, Istituto Auxologico Italiano, Piancavallo, VB, Italy
| | - Giovanna Malchiodi Albedi
- Rehabilitation Unit and Research Lab in Biomechanics and Rehabilitation, S Giuseppe Hospital, Istituto Auxologico Italiano, Piancavallo, VB, Italy
| | - Valentina Aspesi
- Rehabilitation Unit and Research Lab in Biomechanics and Rehabilitation, S Giuseppe Hospital, Istituto Auxologico Italiano, Piancavallo, VB, Italy
| | - Vanessa Merenda
- Rehabilitation Unit and Research Lab in Biomechanics and Rehabilitation, S Giuseppe Hospital, Istituto Auxologico Italiano, Piancavallo, VB, Italy
| | - Manuela Galli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, p.za Leonardo da Vinci 32, 20133 Milan, Italy
| | - Paolo Capodaglio
- Rehabilitation Unit and Research Lab in Biomechanics and Rehabilitation, S Giuseppe Hospital, Istituto Auxologico Italiano, Piancavallo, VB, Italy
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Jackson K, Sample R, Bigelow K. Use of an Instrumented Timed Up and Go (iTUG) for Fall Risk Classification. PHYSICAL & OCCUPATIONAL THERAPY IN GERIATRICS 2018. [DOI: 10.1080/02703181.2018.1528325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- Kurt Jackson
- Department of Physical Therapy, University of Dayton, Ohio, USA
| | - Renee Sample
- Department of Mechanical and Aerospace Engineering, University of Dayton, Ohio, USA
| | - Kimberly Bigelow
- Department of Mechanical and Aerospace Engineering, University of Dayton, Ohio, USA
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Cullen S, Montero-Odasso M, Bherer L, Almeida Q, Fraser S, Muir-Hunter S, Li K, Liu-Ambrose T, McGibbon CA, McIlroy W, Middleton LE, Sarquis-Adamson Y, Beauchet O, McFadyen BJ, Morais JA, Camicioli R. Guidelines for Gait Assessments in the Canadian Consortium on Neurodegeneration in Aging (CCNA). Can Geriatr J 2018; 21:157-165. [PMID: 29977431 PMCID: PMC6028168 DOI: 10.5770/cgj.21.298] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Background Motor and cognitive impairments are common among older adults and often co-exist, increasing their risk of dementia, falls, and fractures. Gait performance is an accepted indicator of global health and it has been proposed as a valid motor marker to detect older adults at risk of developing mobility and cognitive declines including future falls and incident dementia. Our goal was to provide a gait assessment protocol to be used for clinical and research purposes. Methods Based on a consensus that identified common evaluations to assess motor–cognitive interactions in community-dwelling older individuals, a protocol on how to evaluate gait in older adults for the Canadian Consortium on Neurodegeneration in Aging (CCNA) was developed. Results The CCNA gait assessment includes preferred and fast pace gait, and dual-task gait that comprises walking while performing three cognitively demanding tasks: counting backwards by ones, counting backwards by sevens, and naming animals. This gait protocol can be implemented using an electronic-walkway, as well as by using a regular stopwatch. The latter approach provides a simple manner to evaluate quantitative gait performance in clinics. Conclusions Establishing a standardized gait assessment protocol will help to assess motor–cognitive interactions in aging and neurodegeneration, to compare results across studies, and to feasibly implement and translate gait testing in clinics for detecting impending cognitive and mobility decline.
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Affiliation(s)
- Stephanie Cullen
- Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, London, ON, Canada
| | - Manuel Montero-Odasso
- Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, London, ON, Canada.,Schulich School of Medicine and Dentistry, Department of Medicine (Geriatrics) and Department of Epidemiology and Biostatistics, University of Western Ontario, London, ON, Canada
| | - Louis Bherer
- Department of Medicine, Montreal Heart Institute and Institut Universitaire de Gériatrie de Montréal, University of Montreal, Montreal, QC, Canada
| | - Quincy Almeida
- The Sun Life Financial Movement Disorders Research and Rehabilitation Centre, Wilfrid Laurier University, Waterloo, ON, Canada
| | - Sarah Fraser
- Faculty of Health Sciences, Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, ON, Canada
| | - Susan Muir-Hunter
- Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, London, ON, Canada.,Faculty of Health Sciences, School of Physiotherapy, University of Western Ontario, London, ON, Canada
| | - Karen Li
- Department of Psychology, Concordia University, Montreal, QC, Canada
| | - Teresa Liu-Ambrose
- Aging, Mobility, and Cognitive Neuroscience Lab, Department of Physical Therapy, University of British Columbia, Vancouver Coastal Health Research Institute, Vancouver, BC, Canada
| | - Chris A McGibbon
- Faculty of Kinesiology and Institute of Biomedical Engineering, University of New Brunswick, Fredericton, NB, Canada
| | - William McIlroy
- Faculty of Applied Health Sciences, Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada
| | - Laura E Middleton
- Faculty of Applied Health Sciences, Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada
| | - Yanina Sarquis-Adamson
- Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, London, ON, Canada
| | - Olivier Beauchet
- Department of Medicine, Divisions of Geriatrics and Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Bradford J McFadyen
- Rehabilitation Department, Université Laval, and Centre for Interdisciplinary Research in Rehabilitation and Social Integration, Quebec, QC, Canada
| | - José A Morais
- Department of Medicine, Divisions of Geriatrics and Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Richard Camicioli
- Department of Medicine, Division of Neurology, University of Alberta, Edmonton, AB, Canada
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Fleron MK, Ubbesen NCH, Battistella F, Dejtiar DL, Oliveira AS. Accuracy between optical and inertial motion capture systems for assessing trunk speed during preferred gait and transition periods. Sports Biomech 2018; 18:366-377. [PMID: 29327655 DOI: 10.1080/14763141.2017.1409259] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Motion capture through inertial sensors is becoming popular, but its accuracy to describe kinematics during changes in walking speed is unknown. The aim of this study was to determine the accuracy of trunk speed extracted using an inertial motion system compared to a gold standard optical motion system, during steady walking and stationary periods. Eleven participants walked on pre-established paths marked on the floor. Between each lap, a 1-second stationary transition period at the initial position was included prior to the next lap. Resultant trunk speed during the walking and transition periods were extracted from an inertial (240 Hz sampling rate) and an optical system (120 Hz sampling rate) to calculate the agreement (Pearson's correlation coefficient) and relative root mean square errors between both systems. The agreement for the resultant trunk speed between the inertial system and the optical system was strong (0.67 < r ≤ 0.9) for both walking and transition periods. Moreover, relative root mean square error during the transition periods was greater in comparison to the walking periods (>40% across all paths). It was concluded that trunk speed extracted from inertial systems have fair accuracy during walking, but the accuracy was reduced in the transition periods.
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Affiliation(s)
- Martin Kokholm Fleron
- a Faculty of Medicine, Department of Health Science and Technology , Aalborg University , Aalborg , Denmark
| | | | - Francesco Battistella
- a Faculty of Medicine, Department of Health Science and Technology , Aalborg University , Aalborg , Denmark
| | - David Leandro Dejtiar
- a Faculty of Medicine, Department of Health Science and Technology , Aalborg University , Aalborg , Denmark
| | - Anderson Souza Oliveira
- b Faculty of Engineering and Science, Department of Materials and Production , Aalborg University , Aalborg , Denmark
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Automating the Timed Up and Go Test Using a Depth Camera. SENSORS 2017; 18:s18010014. [PMID: 29271926 PMCID: PMC5796464 DOI: 10.3390/s18010014] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Revised: 12/16/2017] [Accepted: 12/19/2017] [Indexed: 11/17/2022]
Abstract
Fall prevention is a human, economic and social issue. The Timed Up and Go (TUG) test is widely used to identify individuals with a high fall risk. However, this test has been criticized because its "diagnostic" is too dependent on the conditions in which it is performed and on the healthcare professionals running it. We used the Microsoft Kinect ambient sensor to automate this test in order to reduce the subjectivity of outcome measures and to provide additional information about patient performance. Each phase of the TUG test was automatically identified from the depth images of the Kinect. Our algorithms accurately measured and assessed the elements usually measured by healthcare professionals. Specifically, average TUG test durations provided by our system differed by only 0.001 s from those measured by clinicians. In addition, our system automatically extracted several additional parameters that allowed us to accurately discriminate low and high fall risk individuals. These additional parameters notably related to the gait and turn pattern, the sitting position and the duration of each phase. Coupling our algorithms to the Kinect ambient sensor can therefore reliably be used to automate the TUG test and perform a more objective, robust and detailed assessment of fall risk.
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Estimating Stair Running Performance Using Inertial Sensors. SENSORS 2017; 17:s17112647. [PMID: 29149063 PMCID: PMC5713493 DOI: 10.3390/s17112647] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Revised: 11/11/2017] [Accepted: 11/13/2017] [Indexed: 11/22/2022]
Abstract
Stair running, both ascending and descending, is a challenging aerobic exercise that many athletes, recreational runners, and soldiers perform during training. Studying biomechanics of stair running over multiple steps has been limited by the practical challenges presented while using optical-based motion tracking systems. We propose using foot-mounted inertial measurement units (IMUs) as a solution as they enable unrestricted motion capture in any environment and without need for external references. In particular, this paper presents methods for estimating foot velocity and trajectory during stair running using foot-mounted IMUs. Computational methods leverage the stationary periods occurring during the stance phase and known stair geometry to estimate foot orientation and trajectory, ultimately used to calculate stride metrics. These calculations, applied to human participant stair running data, reveal performance trends through timing, trajectory, energy, and force stride metrics. We present the results of our analysis of experimental data collected on eleven subjects. Overall, we determine that for either ascending or descending, the stance time is the strongest predictor of speed as shown by its high correlation with stride time.
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Zaferiou AM, Ojeda L, Cain SM, Vitali RV, Davidson SP, Stirling L, Perkins NC. Quantifying performance on an outdoor agility drill using foot-mounted inertial measurement units. PLoS One 2017; 12:e0188184. [PMID: 29145504 PMCID: PMC5690624 DOI: 10.1371/journal.pone.0188184] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Accepted: 11/02/2017] [Indexed: 11/19/2022] Open
Abstract
Running agility is required for many sports and other physical tasks that demand rapid changes in body direction. Quantifying agility skill remains a challenge because measuring rapid changes of direction and quantifying agility skill from those measurements are difficult to do in ways that replicate real task/game play situations. The objectives of this study were to define and to measure agility performance for a (five-cone) agility drill used within a military obstacle course using data harvested from two foot-mounted inertial measurement units (IMUs). Thirty-two recreational athletes ran an agility drill while wearing two IMUs secured to the tops of their athletic shoes. The recorded acceleration and angular rates yield estimates of the trajectories, velocities and accelerations of both feet as well as an estimate of the horizontal velocity of the body mass center. Four agility performance metrics were proposed and studied including: 1) agility drill time, 2) horizontal body speed, 3) foot trajectory turning radius, and 4) tangential body acceleration. Additionally, the average horizontal ground reaction during each footfall was estimated. We hypothesized that shorter agility drill performance time would be observed with small turning radii and large tangential acceleration ranges and body speeds. Kruskal-Wallis and mean rank post-hoc statistical analyses revealed that shorter agility drill performance times were observed with smaller turning radii and larger tangential acceleration ranges and body speeds, as hypothesized. Moreover, measurements revealed the strategies that distinguish high versus low performers. Relative to low performers, high performers used sharper turns, larger changes in body speed (larger tangential acceleration ranges), and shorter duration footfalls that generated larger horizontal ground reactions during the turn phases. Overall, this study advances the use of foot-mounted IMUs to quantify agility performance in contextually-relevant settings (e.g., field of play, training facilities, obstacle courses, etc.).
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Affiliation(s)
- Antonia M. Zaferiou
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Orthopedic Surgery, Rush University Medical Center, Chicago, Illinois, United States of America
- * E-mail:
| | - Lauro Ojeda
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Stephen M. Cain
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Rachel V. Vitali
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Steven P. Davidson
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Leia Stirling
- Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Noel C. Perkins
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
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