1
|
Seong M, Kim G, Yeo D, Kang Y, Yang H, DelPreto J, Matusik W, Rus D, Kim S. MultiSenseBadminton: Wearable Sensor-Based Biomechanical Dataset for Evaluation of Badminton Performance. Sci Data 2024; 11:343. [PMID: 38580698 PMCID: PMC10997636 DOI: 10.1038/s41597-024-03144-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 03/14/2024] [Indexed: 04/07/2024] Open
Abstract
The sports industry is witnessing an increasing trend of utilizing multiple synchronized sensors for player data collection, enabling personalized training systems with multi-perspective real-time feedback. Badminton could benefit from these various sensors, but there is a scarcity of comprehensive badminton action datasets for analysis and training feedback. Addressing this gap, this paper introduces a multi-sensor badminton dataset for forehand clear and backhand drive strokes, based on interviews with coaches for optimal usability. The dataset covers various skill levels, including beginners, intermediates, and experts, providing resources for understanding biomechanics across skill levels. It encompasses 7,763 badminton swing data from 25 players, featuring sensor data on eye tracking, body tracking, muscle signals, and foot pressure. The dataset also includes video recordings, detailed annotations on stroke type, skill level, sound, ball landing, and hitting location, as well as survey and interview data. We validated our dataset by applying a proof-of-concept machine learning model to all annotation data, demonstrating its comprehensive applicability in advanced badminton training and research.
Collapse
Affiliation(s)
- Minwoo Seong
- Gwangju Institute of Science and Technology, School of Integrated Technology, Gwangju, 61005, South Korea
| | - Gwangbin Kim
- Gwangju Institute of Science and Technology, School of Integrated Technology, Gwangju, 61005, South Korea
| | - Dohyeon Yeo
- Gwangju Institute of Science and Technology, School of Integrated Technology, Gwangju, 61005, South Korea
| | - Yumin Kang
- Gwangju Institute of Science and Technology, School of Integrated Technology, Gwangju, 61005, South Korea
| | - Heesan Yang
- Gwangju Institute of Science and Technology, School of Integrated Technology, Gwangju, 61005, South Korea
| | - Joseph DelPreto
- Massachusetts Institute of Technology, CSAIL, Cambridge, MA, 02139, USA
| | - Wojciech Matusik
- Massachusetts Institute of Technology, CSAIL, Cambridge, MA, 02139, USA
| | - Daniela Rus
- Massachusetts Institute of Technology, CSAIL, Cambridge, MA, 02139, USA
| | - SeungJun Kim
- Gwangju Institute of Science and Technology, School of Integrated Technology, Gwangju, 61005, South Korea.
| |
Collapse
|
2
|
Ishida T, Samukawa M. The Difference in the Assessment of Knee Extension/Flexion Angles during Gait between Two Calibration Methods for Wearable Goniometer Sensors. SENSORS (BASEL, SWITZERLAND) 2024; 24:2092. [PMID: 38610306 PMCID: PMC11014198 DOI: 10.3390/s24072092] [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: 02/19/2024] [Revised: 03/22/2024] [Accepted: 03/23/2024] [Indexed: 04/14/2024]
Abstract
Frontal and axial knee motion can affect the accuracy of the knee extension/flexion motion measurement using a wearable goniometer. The purpose of this study was to test the hypothesis that calibrating the goniometer on an individual's body would reduce errors in knee flexion angle during gait, compared to bench calibration. Ten young adults (23.2 ± 1.3 years) were enrolled. Knee flexion angles during gait were simultaneously assessed using a wearable goniometer sensor and an optical three-dimensional motion analysis system, and the absolute error (AE) between the two methods was calculated. The mean AE across a gait cycle was 2.4° (0.5°) for the on-body calibration, and the AE was acceptable (<5°) throughout a gait cycle (range: 1.5-3.8°). The mean AE for the on-bench calibration was 4.9° (3.4°) (range: 1.9-13.6°). Statistical parametric mapping (SPM) analysis revealed that the AE of the on-body calibration was significantly smaller than that of the on-bench calibration during 67-82% of the gait cycle. The results indicated that the on-body calibration of a goniometer sensor had acceptable and better validity compared to the on-bench calibration, especially for the swing phase of gait.
Collapse
Affiliation(s)
| | - Mina Samukawa
- Faculty of Health Sciences, Hokkaido University, North 12, West 5, Kita-ku, Sapporo 060-0812, Japan;
| |
Collapse
|
3
|
Zhang J, Zhao YJ, Wang JY, Cui H, Li S, Meng X, Cai RY, Xie J, Sun SY, Yao Y, Li J. Comprehensive assessment of fine motor movement and cognitive function among older adults in China: a cross-sectional study. BMC Geriatr 2024; 24:118. [PMID: 38297201 PMCID: PMC10832076 DOI: 10.1186/s12877-024-04725-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 01/19/2024] [Indexed: 02/02/2024] Open
Abstract
BACKGROUND Fine motor skills are closely related to cognitive function. However, there is currently no comprehensive assessment of fine motor movement and how it corresponds with cognitive function. To conduct a complete assessment of fine motor and clarify the relationship between various dimensions of fine motor and cognitive function. METHODS We conducted a cross-sectional study with 267 community-based participants aged ≥ 60 years in Beijing, China. We assessed four tests performance and gathered detailed fine motor indicators using Micro-Electro-Mechanical System (MEMS) motion capture technology. The wearable MEMS device provided us with precise fine motion metrics, while Chinese version of the Montreal Cognitive Assessment (MoCA) was used to assess cognitive function. We adopted logistic regression to analyze the relationship between fine motor movement and cognitive function. RESULTS 129 (48.3%) of the participants had cognitive impairment. The vast majority of fine motor movements have independent linear correlations with MoCA-BJ scores. According to logistic regression analysis, completion time in the Same-pattern tapping test (OR = 1.033, 95%CI = 1.003-1.063), Completion time of non-dominant hand in the Pieces flipping test (OR = 1.006, 95%CI = 1.000-1.011), and trajectory distance of dominant hand in the Pegboard test (OR = 1.044, 95%CI = 1.010-1.068), which represents dexterity, are related to cognitive impairment. Coordination, represented by lag time between hands in the Same-pattern tapping (OR = 1.663, 95%CI = 1.131-2.444), is correlated with cognitive impairment. Coverage in the Dual-hand drawing test as an important indicator of stability is negatively correlated with cognitive function (OR = 0.709, 95%CI = 0.6501-0.959). Based on the above 5-feature model showed consistently high accuracy and sensitivity at the MoCA-BJ score (ACU = 0.80-0.87). CONCLUSIONS The results of a comprehensive fine-motor assessment that integrates dexterity, coordination, and stability are closely related to cognitive functioning. Fine motor movement has the potential to be a reliable predictor of cognitive impairment.
Collapse
Affiliation(s)
- Jie Zhang
- Department of Geriatric Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, P. R. China
| | - Ye-Jing Zhao
- Department of Geriatric Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, P. R. China
| | | | - Han Cui
- Department of Geriatric Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, P. R. China
| | - Shaojie Li
- China Center for Health Development Studies, Peking University, Beijing, China
| | - Xue Meng
- Office of the National Clinical Research Center for Geriatric Diseases, Beijing Hospital, Institute of Geriatric Medicine, National Center of Gerontology, Chinese Academy of Medical Sciences, Beijing, P. R. China
| | - Rui-Yu Cai
- Department of Geriatric Medicine, Zhucheng People's Hospital, Weifang City, Shandong Province, China
| | - Juan Xie
- Geriatric Department, Hefei First People's Hospital, Hefei, China
| | - Su-Ya Sun
- Department of Geriatrics, Tangshan Gong Ren Hospital, Tangshan, Hebei, China
| | - Yao Yao
- China Center for Health Development Studies, Peking University, Beijing, China.
| | - Jing Li
- Department of Geriatric Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, P. R. China.
| |
Collapse
|
4
|
Wu Y, Shen Y, Tian Y, Chen Q, Sun L. Quantifying the effects of ice hockey upper body pads on mobility and comfort. iScience 2024; 27:108606. [PMID: 38169817 PMCID: PMC10758976 DOI: 10.1016/j.isci.2023.108606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 09/05/2023] [Accepted: 11/29/2023] [Indexed: 01/05/2024] Open
Abstract
Ice hockey is a high-intensity sport in which pads such as shoulder and elbow pads (S/EPs) are necessary to help players avoid injury. However, they can also affect mobility and comfort, thereby affecting players' on-ice performance. We aimed to quantify the effects of S/EPs on mobility and comfort by comparing the range of motion (ROM) of nine elite college-level ice hockey players performing static (nine single-DOF upper-body movements) and dynamic (wrist and slap shots) tasks under six pad conditions (no S/EPs and five types of S/EPs). We also analyzed the relationship between ROM and subjective comfort to provide an objective comfort evaluation of hockey pads. Five types of S/EPs restrict ROM at different levels, imposing additional mobility restrictions. We found significant differences among the five types and a high correlation between comfort and ROM. We conducted a comprehensive evaluation of the impact of ice hockey pads on mobility and comfort.
Collapse
Affiliation(s)
- Yiwei Wu
- AI Sports Engineering Lab, School of Sports Engineering, Beijing Sport University, Beijing 100084, China
| | - Yanfei Shen
- AI Sports Engineering Lab, School of Sports Engineering, Beijing Sport University, Beijing 100084, China
| | - Yinsheng Tian
- AI Sports Engineering Lab, School of Sports Engineering, Beijing Sport University, Beijing 100084, China
| | - Qi Chen
- Sports Engineering Research Center, China Institute of Sport Science, Beijing 100061, China
| | - Lixin Sun
- AI Sports Engineering Lab, School of Sports Engineering, Beijing Sport University, Beijing 100084, China
| |
Collapse
|
5
|
Ino T, Samukawa M, Ishida T, Wada N, Koshino Y, Kasahara S, Tohyama H. Validity of AI-Based Gait Analysis for Simultaneous Measurement of Bilateral Lower Limb Kinematics Using a Single Video Camera. SENSORS (BASEL, SWITZERLAND) 2023; 23:9799. [PMID: 38139644 PMCID: PMC10747245 DOI: 10.3390/s23249799] [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: 11/16/2023] [Revised: 12/02/2023] [Accepted: 12/12/2023] [Indexed: 12/24/2023]
Abstract
Accuracy validation of gait analysis using pose estimation with artificial intelligence (AI) remains inadequate, particularly in objective assessments of absolute error and similarity of waveform patterns. This study aimed to clarify objective measures for absolute error and waveform pattern similarity in gait analysis using pose estimation AI (OpenPose). Additionally, we investigated the feasibility of simultaneous measuring both lower limbs using a single camera from one side. We compared motion analysis data from pose estimation AI using video footage that was synchronized with a three-dimensional motion analysis device. The comparisons involved mean absolute error (MAE) and the coefficient of multiple correlation (CMC) to compare the waveform pattern similarity. The MAE ranged from 2.3 to 3.1° on the camera side and from 3.1 to 4.1° on the opposite side, with slightly higher accuracy on the camera side. Moreover, the CMC ranged from 0.936 to 0.994 on the camera side and from 0.890 to 0.988 on the opposite side, indicating a "very good to excellent" waveform similarity. Gait analysis using a single camera revealed that the precision on both sides was sufficiently robust for clinical evaluation, while measurement accuracy was slightly superior on the camera side.
Collapse
Affiliation(s)
- Takumi Ino
- Graduate School of Health Sciences, Hokkaido University, Sapporo 0600812, Japan;
- Department of Physical Therapy, Faculty of Health Sciences, Hokkaido University of Science, Sapporo 0068585, Japan
| | - Mina Samukawa
- Faculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan
| | - Tomoya Ishida
- Faculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan
| | - Naofumi Wada
- Department of Information and Computer Science, Faculty of Engineering, Hokkaido University of Science, Sapporo 0068585, Japan;
| | - Yuta Koshino
- Faculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan
| | - Satoshi Kasahara
- Faculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan
| | - Harukazu Tohyama
- Faculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan
| |
Collapse
|
6
|
Antonacci C, Longo UG, Nazarian A, Schena E, Carnevale A. Monitoring Scapular Kinematics through Wearable Magneto-Inertial Measurement Units: State of the Art and New Frontiers. SENSORS (BASEL, SWITZERLAND) 2023; 23:6940. [PMID: 37571723 PMCID: PMC10422625 DOI: 10.3390/s23156940] [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: 07/07/2023] [Revised: 07/31/2023] [Accepted: 08/02/2023] [Indexed: 08/13/2023]
Abstract
Monitoring shoulder kinematics, including the scapular segment, is of great relevance in the orthopaedic field. Among wearable systems, magneto-inertial measurement units (M-IMUs) represent a valid alternative for applications in unstructured environments. The aim of this systematic literature review is to report and describe the existing methods to estimate 3D scapular movements through wearable systems integrating M-IMUs. A comprehensive search of PubMed, IEEE Xplore, and Web of Science was performed, and results were included up to May 2023. A total of 14 articles was included. The results showed high heterogeneity among studies regarding calibration procedures, tasks executed, and the population. Two different techniques were described, i.e., with the x-axis aligned with the cranial edge of the scapular spine or positioned on the flat surface of the acromion with the x-axis perpendicular to the scapular spine. Sensor placement affected the scapular motion and, also, the kinematic output. Further studies should be conducted to establish a universal protocol that reduces the variability among studies. Establishing a protocol that can be carried out without difficulty or pain by patients with shoulder musculoskeletal disorders could be of great clinical relevance for patients and clinicians to monitor 3D scapular kinematics in unstructured settings or during common clinical practice.
Collapse
Affiliation(s)
- Carla Antonacci
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Álvaro del Portillo, 200, 00128 Roma, Italy; (C.A.); (A.C.)
- Unit of Measurements and Biomedical Instrumentation, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo, 21, 00128 Roma, Italy;
| | - Umile Giuseppe Longo
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Álvaro del Portillo, 200, 00128 Roma, Italy; (C.A.); (A.C.)
- Research Unit of Orthopaedic and Trauma Surgery, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo, 21, 00128 Roma, Italy
| | - Ara Nazarian
- Carl J. Shapiro Department of Orthopaedic Surgery and Center for Advanced Orthopaedic Studies, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 20115, USA;
| | - Emiliano Schena
- Unit of Measurements and Biomedical Instrumentation, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo, 21, 00128 Roma, Italy;
| | - Arianna Carnevale
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Álvaro del Portillo, 200, 00128 Roma, Italy; (C.A.); (A.C.)
| |
Collapse
|
7
|
Yamagata M, Nagai R, Morihiro K, Nonaka T. Relation between the kinematic synergy controlling swing foot and visual exploration during obstacle crossing. J Biomech 2023; 157:111702. [PMID: 37429178 DOI: 10.1016/j.jbiomech.2023.111702] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 05/24/2023] [Accepted: 06/26/2023] [Indexed: 07/12/2023]
Abstract
To step over obstacles of varying heights, two distinct ongoing streams of activities-visual exploration of the environment and gait adjustment- were required to occur concurrently without interfering each other. Yet, it remains unclear whether and how the manner of embodied behavior of visual exploration is related to the synergistic control of foot trajectory to negotiate with the irregular terrain. Thus, we aimed to explore that how the synergistic control of the vertical trajectory of the swing foot (i.e., obstacle clearance) crossing an obstacle is related to the manner of visual exploration of the environment during approach. Twenty healthy young adults crossed an obstacle (depth: 1 cm, width: 60 cm, height: 8 cm) during their comfortable-speed walking. The visual exploration was evaluated as the amount of time spent in fixating the vicinity of the obstacle on the floor during the period from two to four steps prior to crossing the obstacle, and the strengths of kinematic synergy to control obstacle clearance were estimated using the uncontrolled manifold approach. We found that the participants with relatively weak synergy spent more time fixating at the vicinity of the obstacle from two to four steps prior to crossing the obstacle, and those participants exhibited greater amount of head flexion movement compared to those with stronger kinematic synergy. Taking advantage of this complex relationship between exploratory activities (e.g. looking movement) and performative activities (e.g. adjustment of ground clearance) would be crucial to adapt walking in a complex environment.
Collapse
Affiliation(s)
- Momoko Yamagata
- Faculty of Rehabilitation, Kansai Medical University, 18-89 Uyama Higashimachi, Hirakata, Osaka 573-1136, Japan; Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, 53 Kawahara-cho, Shogoin, Sakyo Kyoto 606-8507, Japan.
| | - Rira Nagai
- Department of Human Development, Graduate School of Human Development and Environment, Kobe University, 3-11 Tsurukabuto, Nada-ku, Kobe, Hyogo 657-0011, Japan
| | - Kaoru Morihiro
- Department of Human Development, Graduate School of Human Development and Environment, Kobe University, 3-11 Tsurukabuto, Nada-ku, Kobe, Hyogo 657-0011, Japan
| | - Tetsushi Nonaka
- Department of Human Development, Graduate School of Human Development and Environment, Kobe University, 3-11 Tsurukabuto, Nada-ku, Kobe, Hyogo 657-0011, Japan
| |
Collapse
|
8
|
Qi J, Li D, He J, Wang Y. Optically Non-Contact Cross-Country Skiing Action Recognition Based on Key-Point Collaborative Estimation and Motion Feature Extraction. SENSORS (BASEL, SWITZERLAND) 2023; 23:3639. [PMID: 37050699 PMCID: PMC10098931 DOI: 10.3390/s23073639] [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: 02/05/2023] [Revised: 03/29/2023] [Accepted: 03/29/2023] [Indexed: 06/19/2023]
Abstract
Technical motion recognition in cross-country skiing can effectively help athletes to improve their skiing movements and optimize their skiing strategies. The non-contact acquisition method of the visual sensor has a bright future in ski training. The changing posture of the athletes, the environment of the ski resort, and the limited field of view have posed great challenges for motion recognition. To improve the applicability of monocular optical sensor-based motion recognition in skiing, we propose a monocular posture detection method based on cooperative detection and feature extraction. Our method uses four feature layers of different sizes to simultaneously detect human posture and key points and takes the position deviation loss and rotation compensation loss of key points as the loss function to implement the three-dimensional estimation of key points. Then, according to the typical characteristics of cross-country skiing movement stages and major sub-movements, the key points are divided and the features are extracted to implement the ski movement recognition. The experimental results show that our method is 90% accurate for cross-country skiing movements, which is equivalent to the recognition method based on wearable sensors. Therefore, our algorithm has application value in the scientific training of cross-country skiing.
Collapse
Affiliation(s)
- Jiashuo Qi
- Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China
| | - Dongguang Li
- Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China
| | - Jian He
- School of Mechatronic and Electrical Engineering, North University of China, Taiyuan 030051, China
| | - Yu Wang
- Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China
| |
Collapse
|
9
|
Ishida T, Samukawa M. Validity and Reliability of a Wearable Goniometer Sensor Controlled by a Mobile Application for Measuring Knee Flexion/Extension Angle during the Gait Cycle. SENSORS (BASEL, SWITZERLAND) 2023; 23:3266. [PMID: 36991977 PMCID: PMC10059898 DOI: 10.3390/s23063266] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 03/10/2023] [Accepted: 03/16/2023] [Indexed: 06/19/2023]
Abstract
Knee kinematics during gait is an important assessment tool in health-promotion and clinical fields. This study aimed to determine the validity and reliability of a wearable goniometer sensor for measuring knee flexion angles throughout the gait cycle. Twenty-two and seventeen participants were enrolled in the validation and reliability study, respectively. The knee flexion angle during gait was assessed using a wearable goniometer sensor and a standard optical motion analysis system. The coefficient of multiple correlation (CMC) between the two measurement systems was 0.992 ± 0.008. Absolute error (AE) was 3.3 ± 1.5° (range: 1.3-6.2°) for the entire gait cycle. An acceptable AE (<5°) was observed during 0-65% and 87-100% of the gait cycle. Discrete analysis revealed a significant correlation between the two systems (R = 0.608-0.904, p ≤ 0.001). The CMC between the two measurement days with a 1-week interval was 0.988 ± 0.024, and the AE was 2.5 ± 1.2° (range: 1.1-4.5°). A good-to-acceptable AE (<5°) was observed throughout the gait cycle. These results indicate that the wearable goniometer sensor is useful for assessing knee flexion angle during the stance phase of the gait cycle.
Collapse
Affiliation(s)
| | - Mina Samukawa
- Faculty of Health Sciences, Hokkaido University, North 12, West 5, Kita-ku, Sapporo 060-0812, Japan
| |
Collapse
|
10
|
Wang F, Dong A, Zhang K, Qian D, Tian Y. A Quantitative Assessment Grading Study of Balance Performance Based on Lower Limb Dataset. SENSORS (BASEL, SWITZERLAND) 2022; 23:33. [PMID: 36616632 PMCID: PMC9824022 DOI: 10.3390/s23010033] [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: 11/01/2022] [Revised: 12/07/2022] [Accepted: 12/17/2022] [Indexed: 06/17/2023]
Abstract
Balance ability is one of the important factors in measuring human physical fitness and a common index for evaluating sports performance. Its quality directly affects the coordination ability of human movements and plays an important role in human productive activities. In the field of sports, balance ability is an important indicator of athletes' selection and training. How to objectively analyze balance performance becomes a problem for every non-professional sports enthusiast. Therefore, in this paper, we used a dataset of lower limb collected by inertial sensors to extract the feature parameters, then designed a RUS Boost classifier for unbalanced data whose basic classifier was SVM model to predict three classifications of balance degree, and, finally, evaluated the performance of the new classifier by comparing it with two basic classifiers (KNN, SVM). The result showed that the new classifier could be used to evaluate the balanced ability of lower limb, and performed higher than basic ones (RUS Boost: 72%; KNN: 60%; SVM: 44%). The results meant the established classification model could be used for and quantitative assessment of balance ability in initial screening and targeted training.
Collapse
|
11
|
Wu Y, Tao K, Chen Q, Tian Y, Sun L. A Comprehensive Analysis of the Validity and Reliability of the Perception Neuron Studio for Upper-Body Motion Capture. SENSORS (BASEL, SWITZERLAND) 2022; 22:6954. [PMID: 36146301 PMCID: PMC9506133 DOI: 10.3390/s22186954] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 09/08/2022] [Accepted: 09/13/2022] [Indexed: 06/16/2023]
Abstract
The Perception Neuron Studio (PNS) is a cost-effective and widely used inertial motion capture system. However, a comprehensive analysis of its upper-body motion capture accuracy is still lacking, before it is being applied to biomechanical research. Therefore, this study first evaluated the validity and reliability of this system in upper-body capturing and then quantified the system's accuracy for different task complexities and movement speeds. Seven participants performed simple (eight single-DOF upper-body movements) and complex tasks (lifting a 2.5 kg box over the shoulder) at fast and slow speeds with the PNS and OptiTrack (gold-standard optical system) collecting kinematics data simultaneously. Statistical metrics such as CMC, RMSE, Pearson's r, R2, and Bland-Altman analysis were utilized to assess the similarity between the two systems. Test-retest reliability included intra- and intersession relations, which were assessed by the intraclass correlation coefficient (ICC) as well as CMC. All upper-body kinematics were highly consistent between the two systems, with CMC values 0.73-0.99, RMSE 1.9-12.5°, Pearson's r 0.84-0.99, R2 0.75-0.99, and Bland-Altman analysis demonstrating a bias of 0.2-27.8° as well as all the points within 95% limits of agreement (LOA). The relative reliability of intra- and intersessions was good to excellent (i.e., ICC and CMC were 0.77-0.99 and 0.75-0.98, respectively). The paired t-test revealed that faster speeds resulted in greater bias, while more complex tasks led to lower consistencies. Our results showed that the PNS could provide accurate enough upper-body kinematics for further biomechanical performance analysis.
Collapse
Affiliation(s)
- Yiwei Wu
- AI Sports Engineering Lab, School of Sports Engineering, Beijing Sport University, Beijing 100084, China
| | - Kuan Tao
- AI Sports Engineering Lab, School of Sports Engineering, Beijing Sport University, Beijing 100084, China
| | - Qi Chen
- Sports Engineering Research Center, China Institute of Sport Science, Beijing 100061, China
| | - Yinsheng Tian
- AI Sports Engineering Lab, School of Sports Engineering, Beijing Sport University, Beijing 100084, China
| | - Lixin Sun
- AI Sports Engineering Lab, School of Sports Engineering, Beijing Sport University, Beijing 100084, China
| |
Collapse
|
12
|
Predicting Coordination Variability of Selected Lower Extremity Couplings during a Cutting Movement: An Investigation of Deep Neural Networks with the LSTM Structure. Bioengineering (Basel) 2022; 9:bioengineering9090411. [PMID: 36134957 PMCID: PMC9495438 DOI: 10.3390/bioengineering9090411] [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: 07/06/2022] [Revised: 08/15/2022] [Accepted: 08/19/2022] [Indexed: 11/17/2022] Open
Abstract
There are still few portable methods for monitoring lower limb joint coordination during the cutting movements (CM). This study aims to obtain the relevant motion biomechanical parameters of the lower limb joints at 90°, 135°, and 180° CM by collecting IMU data of the human lower limbs, and utilizing the Long Short-Term Memory (LSTM) deep neural-network framework to predict the coordination variability of selected lower extremity couplings at the three CM directions. There was a significant (p < 0.001) difference between the three couplings during the swing, especially at 90° vs the other directions. At 135° and 180°, t13-he coordination variability of couplings was significantly greater than at 90° (p < 0.001). It is important to note that the coordination variability of Hip rotation/Knee flexion-extension was significantly higher at 90° than at 180° (p < 0.001). By the LSTM, the CM coordination variability for 90° (CMC = 0.99063, RMSE = 0.02358), 135° (CMC = 0.99018, RMSE = 0.02465) and 180° (CMC = 0.99485, RMSE = 0.01771) were accurately predicted. The predictive model could be used as a reliable tool for predicting the coordination variability of different CM directions in patients or athletes and real-world open scenarios using inertial sensors.
Collapse
|
13
|
Di Raimondo G, Vanwanseele B, van der Have A, Emmerzaal J, Willems M, Killen BA, Jonkers I. Inertial Sensor-to-Segment Calibration for Accurate 3D Joint Angle Calculation for Use in OpenSim. SENSORS 2022; 22:s22093259. [PMID: 35590949 PMCID: PMC9104520 DOI: 10.3390/s22093259] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 04/19/2022] [Accepted: 04/21/2022] [Indexed: 01/08/2023]
Abstract
Inertial capture (InCap) systems combined with musculoskeletal (MSK) models are an attractive option for monitoring 3D joint kinematics in an ecological context. However, the primary limiting factor is the sensor-to-segment calibration, which is crucial to estimate the body segment orientations. Walking, running, and stair ascent and descent trials were measured in eleven healthy subjects with the Xsens InCap system and the Vicon 3D motion capture (MoCap) system at a self-selected speed. A novel integrated method that combines previous sensor-to-segment calibration approaches was developed for use in a MSK model with three degree of freedom (DOF) hip and knee joints. The following were compared: RMSE, range of motion (ROM), peaks, and R2 between InCap kinematics estimated with different calibration methods and gold standard MoCap kinematics. The integrated method reduced the RSME for both the hip and the knee joints below 5°, and no statistically significant differences were found between MoCap and InCap kinematics. This was consistent across all the different analyzed movements. The developed method was integrated on an MSK model workflow, and it increased the sensor-to-segment calibration accuracy for an accurate estimate of 3D joint kinematics compared to MoCap, guaranteeing a clinical easy-to-use approach.
Collapse
|