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Filippou V, Backhouse MR, Redmond AC, Wong DC. Person-Specific Template Matching Using a Dynamic Time Warping Step-Count Algorithm for Multiple Walking Activities. SENSORS (BASEL, SWITZERLAND) 2023; 23:9061. [PMID: 38005449 PMCID: PMC10675039 DOI: 10.3390/s23229061] [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: 09/27/2023] [Revised: 10/22/2023] [Accepted: 11/07/2023] [Indexed: 11/26/2023]
Abstract
This study aimed to develop and evaluate a new step-count algorithm, StepMatchDTWBA, for the accurate measurement of physical activity using wearable devices in both healthy and pathological populations. We conducted a study with 30 healthy volunteers wearing a wrist-worn MOX accelerometer (Maastricht Instruments, NL). The StepMatchDTWBA algorithm used dynamic time warping (DTW) barycentre averaging to create personalised templates for representative steps, accounting for individual walking variations. DTW was then used to measure the similarity between the template and accelerometer epoch. The StepMatchDTWBA algorithm had an average root-mean-square error of 2 steps for healthy gaits and 12 steps for simulated pathological gaits over a distance of about 10 m (GAITRite walkway) and one flight of stairs. It outperformed benchmark algorithms for the simulated pathological population, showcasing the potential for improved accuracy in personalised step counting for pathological populations. The StepMatchDTWBA algorithm represents a significant advancement in accurate step counting for both healthy and pathological populations. This development holds promise for creating more precise and personalised activity monitoring systems, benefiting various health and wellness applications.
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Affiliation(s)
- Valeria Filippou
- Institute of Medical and Biological Engineering, University of Leeds, Leeds LS2 9JT, UK
| | | | - Anthony C. Redmond
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds LS2 9JT, UK;
| | - David C. Wong
- Leeds Institute of Health Informatics, University of Leeds, Leeds LS2 9JT, UK;
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2
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Cabaraux P, Agrawal SK, Cai H, Calabro RS, Casali C, Damm L, Doss S, Habas C, Horn AKE, Ilg W, Louis ED, Mitoma H, Monaco V, Petracca M, Ranavolo A, Rao AK, Ruggieri S, Schirinzi T, Serrao M, Summa S, Strupp M, Surgent O, Synofzik M, Tao S, Terasi H, Torres-Russotto D, Travers B, Roper JA, Manto M. Consensus Paper: Ataxic Gait. CEREBELLUM (LONDON, ENGLAND) 2022; 22:394-430. [PMID: 35414041 DOI: 10.1007/s12311-022-01373-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/20/2022] [Indexed: 12/19/2022]
Abstract
The aim of this consensus paper is to discuss the roles of the cerebellum in human gait, as well as its assessment and therapy. Cerebellar vermis is critical for postural control. The cerebellum ensures the mapping of sensory information into temporally relevant motor commands. Mental imagery of gait involves intrinsically connected fronto-parietal networks comprising the cerebellum. Muscular activities in cerebellar patients show impaired timing of discharges, affecting the patterning of the synergies subserving locomotion. Ataxia of stance/gait is amongst the first cerebellar deficits in cerebellar disorders such as degenerative ataxias and is a disabling symptom with a high risk of falls. Prolonged discharges and increased muscle coactivation may be related to compensatory mechanisms and enhanced body sway, respectively. Essential tremor is frequently associated with mild gait ataxia. There is growing evidence for an important role of the cerebellar cortex in the pathogenesis of essential tremor. In multiple sclerosis, balance and gait are affected due to cerebellar and spinal cord involvement, as a result of disseminated demyelination and neurodegeneration impairing proprioception. In orthostatic tremor, patients often show mild-to-moderate limb and gait ataxia. The tremor generator is likely located in the posterior fossa. Tandem gait is impaired in the early stages of cerebellar disorders and may be particularly useful in the evaluation of pre-ataxic stages of progressive ataxias. Impaired inter-joint coordination and enhanced variability of gait temporal and kinetic parameters can be grasped by wearable devices such as accelerometers. Kinect is a promising low cost technology to obtain reliable measurements and remote assessments of gait. Deep learning methods are being developed in order to help clinicians in the diagnosis and decision-making process. Locomotor adaptation is impaired in cerebellar patients. Coordinative training aims to improve the coordinative strategy and foot placements across strides, cerebellar patients benefiting from intense rehabilitation therapies. Robotic training is a promising approach to complement conventional rehabilitation and neuromodulation of the cerebellum. Wearable dynamic orthoses represent a potential aid to assist gait. The panel of experts agree that the understanding of the cerebellar contribution to gait control will lead to a better management of cerebellar ataxias in general and will likely contribute to use gait parameters as robust biomarkers of future clinical trials.
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Affiliation(s)
- Pierre Cabaraux
- Unité Des Ataxies Cérébelleuses, Department of Neurology, CHU de Charleroi, Charleroi, Belgium.
| | | | - Huaying Cai
- Department of Neurology, Neuroscience Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China
| | | | - Carlo Casali
- Department of Medico-Surgical Sciences and Biotechnologies, University of Rome Sapienza, Latina, Italy
| | - Loic Damm
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France
| | - Sarah Doss
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, USA
| | - Christophe Habas
- Université Versailles Saint-Quentin, Versailles, France.,Service de NeuroImagerie, Centre Hospitalier National des 15-20, Paris, France
| | - Anja K E Horn
- Institute of Anatomy and Cell Biology I, Ludwig Maximilians-University Munich, Munich, Germany
| | - Winfried Ilg
- Section Computational Sensomotorics, Hertie Institute for Clinical Brain Research, University Tübingen, Tübingen, Germany
| | - Elan D Louis
- Department of Neurology, University of Texas Southwestern, Dallas, TX, USA
| | - Hiroshi Mitoma
- Department of Medical Education, Tokyo Medical University, Tokyo, Japan
| | - Vito Monaco
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Maria Petracca
- Department of Human Neurosciences, University of Rome Sapienza, Rome, Italy
| | - Alberto Ranavolo
- Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, INAIL, Monte Porzio Catone, Rome, Italy
| | - Ashwini K Rao
- Department of Rehabilitation & Regenerative Medicine (Programs in Physical Therapy), Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Serena Ruggieri
- Department of Human Neurosciences, University of Rome Sapienza, Rome, Italy.,Neuroimmunology Unit, IRCSS Fondazione Santa Lucia, Rome, Italy
| | - Tommaso Schirinzi
- Department of Systems Medicine, University of Roma Tor Vergata, Rome, Italy
| | - Mariano Serrao
- Department of Medico-Surgical Sciences and Biotechnologies, University of Rome Sapienza, Latina, Italy.,Movement Analysis LAB, Policlinico Italia, Rome, Italy
| | - Susanna Summa
- MARlab, Neuroscience and Neurorehabilitation Department, Bambino Gesù Children's Hospital - IRCCS, Rome, Italy
| | - Michael Strupp
- Department of Neurology and German Center for Vertigo and Balance Disorders, Hospital of the Ludwig Maximilians-University Munich, Munich, Germany
| | - Olivia Surgent
- Neuroscience Training Program and Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Matthis Synofzik
- Department of Neurodegeneration, Hertie Institute for Clinical Brain Research and Centre of Neurology, Tübingen, Germany
| | - Shuai Tao
- Dalian Key Laboratory of Smart Medical and Health, Dalian University, Dalian, 116622, China
| | - Hiroo Terasi
- Department of Neurology, Tokyo Medical University, Tokyo, Japan
| | - Diego Torres-Russotto
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, USA
| | - Brittany Travers
- Department of Kinesiology and Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Jaimie A Roper
- School of Kinesiology, Auburn University, Auburn, AL, USA
| | - Mario Manto
- Unité Des Ataxies Cérébelleuses, Department of Neurology, CHU de Charleroi, Charleroi, Belgium.,Service Des Neurosciences, University of Mons, UMons, Mons, Belgium
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3
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Analysis of time series of surface electromyography and accelerometry in dogs. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2022.103518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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4
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Rudisch J, Jöllenbeck T, Vogt L, Cordes T, Klotzbier TJ, Vogel O, Wollesen B. Agreement and consistency of five different clinical gait analysis systems in the assessment of spatiotemporal gait parameters. Gait Posture 2021; 85:55-64. [PMID: 33516094 DOI: 10.1016/j.gaitpost.2021.01.013] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 01/11/2021] [Accepted: 01/14/2021] [Indexed: 02/02/2023]
Abstract
BACKGROUND Measuring gait function has become an essential tool in the assessment of mobility in aging populations for both, clinicians and researchers. A variety of systems exist that assess gait parameters such as gait cycle time, gait speed or duration of relative gait phases. Due to different measurement principles such as inertial or pressure sensors, accurate detection of spatiotemporal events may vary between systems. RESEARCH QUESTION To compare the absolute agreement and consistency in spatiotemporal gait parameters among five different clinical gait analysis systems using different sensor technologies. METHODS We compared two devices using inertial sensors (GaitUp & Mobility Lab), two devices using pressure sensor systems (GAITRite & Zebris) as well as one optical system (OptoGait). Twelve older adults walked at self-selected speed through a walkway integrating all of the above systems. Basic spatiotemporal parameters (gait cycle time, cadence, gait speed and stride length) as well as measures of relative phase (stance phase, swing phase, double stance phase, single limb support) were extracted from all systems. We used Intraclass Correlation Coefficients as measures of agreement and consistency. RESULTS High agreement and consistency between all systems was found for basic spatiotemporal parameters, whereas parameters of relative phase showed poorer agreement and consistency. Overground measurement (GAITRite & OptoGait) showed generally higher agreement with each other as compared to inertial sensor-based systems. SIGNIFICANCE Our results indicate that accurate detection of both, the heel-strike and toe-off event are crucial for reliable results. Systematic errors in the detection of one or both events may only have a small impact on basic spatiotemporal outcomes as errors remain consistent from step to step. Relative phase parameters on the other hand may be affected to a much larger extent as these differences lead to a systematic increase or reduction of relative phase durations.
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Affiliation(s)
- Julian Rudisch
- Department of Neuromotor Behavior and Exercise, Institute of Sport and Exercise Sciences, University of Münster, Horstmarer Landweg 62B, 48149 Münster, Germany.
| | - Thomas Jöllenbeck
- Institute for Biomechanics, Clinic Lindenplatz, Weslarner Str. 29, 59505 Bad Sassendorf, Germany; Department of Exercise & Health, University of Paderborn, Warburger Straße 100, 33098 Paderborn, Germany.
| | - Lutz Vogt
- Department of Sports Medicine, Goethe University Frankfurt am Main, Ginnheimer Landstr. 39, 60487 Frankfurt, Germany.
| | - Thomas Cordes
- Department of Human Movement Science, University of Hamburg, Mollerstraße 10, 20148 Hamburg, Germany.
| | - Thomas Jürgen Klotzbier
- Department of Sport and Exercise Science, University of Stuttgart, Allmandring 28, 70569 Stuttgart, Germany.
| | - Oliver Vogel
- Department of Sports Medicine, Goethe University Frankfurt am Main, Ginnheimer Landstr. 39, 60487 Frankfurt, Germany.
| | - Bettina Wollesen
- Department of Human Movement Science, University of Hamburg, Mollerstraße 10, 20148 Hamburg, Germany; Biological Psychology and Neuroergonomics, TU Berlin, Fasanenstr. 1, 10623 Berlin, Germany.
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Vienne-Jumeau A, Oudre L, Moreau A, Quijoux F, Edmond S, Dandrieux M, Legendre E, Vidal PP, Ricard D. Personalized Template-Based Step Detection From Inertial Measurement Units Signals in Multiple Sclerosis. Front Neurol 2020; 11:261. [PMID: 32373047 PMCID: PMC7186475 DOI: 10.3389/fneur.2020.00261] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 03/20/2020] [Indexed: 01/21/2023] Open
Abstract
Background: Objective gait assessment is key for the follow-up of patients with progressive multiple sclerosis (pMS). Inertial measurement units (IMUs) provide reliable and yet easy quantitative gait assessment in routine clinical settings. However, to the best of our knowledge, no automated step-detection algorithm performs well in detecting severely altered pMS gait. Method: This article elaborates on a step-detection method based on personalized templates tested against a gold standard. Twenty-two individuals with pMS and 10 young healthy subjects (HSs) were instructed to walk on an electronic walkway wearing synchronized IMUs. Templates were derived from the IMU signals by using Initial and Final Contact times given by the walkway. These were used to detect steps from other gait trials of the same individual (intra-individual template-based detection, IITD) or another participant from the same group (pMS or HS) (intra-group template-based detection, IGTD). All participants were seen twice with a 6-month interval, with two measurements performed at each visit. Performance and accuracy metrics were computed, along with a similarity index (SId), which was computed as the mean distance between detected steps and their respective closest template. Results: For HS participants, both the IITD and the IGTD algorithms had precision and recall of 1.00 for detecting steps. For pMS participants, precision and recall ranged from 0.94 to 1.00 for IITD and 0.85 to 0.95 for IGTD depending on the level of disability. The SId was correlated with performance and the accuracy of the result. An SId threshold of 0.957 (IITD) and 0.963 (IGTD) could rule out decreased performance (F-measure ≤ 0.95), with negative predictive values of 0.99 and 0.96 with the IITD and IGTD algorithms. Also, the SId computed with the IITD and IGTD algorithms could distinguish individuals showing changes at 6-month follow-up. Conclusion: This personalized step-detection method has high performance for detecting steps in pMS individuals with severely altered gait. The algorithm can be self-evaluating with the SI, which gives a measure of the confidence the clinician can have in the detection. What is more, the SId can be used as a biomarker of change in disease severity occurring between the two measurement times.
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Affiliation(s)
- Aliénor Vienne-Jumeau
- COGNAC-G (UMR 8257), CNRS Service de Santé des Armées, University Paris Descartes, Paris, France
| | - Laurent Oudre
- COGNAC-G (UMR 8257), CNRS Service de Santé des Armées, University Paris Descartes, Paris, France.,L2TI, University Paris 13, Villetaneuse, France.,CMLA (UMR 8536), CNRS ENS Paris-Saclay, Cachan, France
| | - Albane Moreau
- Service de Neurologie, Hôpital d'Instruction des Armées Percy, Service de Santé des Armées, Clamart, France
| | - Flavien Quijoux
- COGNAC-G (UMR 8257), CNRS Service de Santé des Armées, University Paris Descartes, Paris, France.,ORPEA Group, Puteaux, France
| | - Sébastien Edmond
- Service de Neurologie, Hôpital d'Instruction des Armées Percy, Service de Santé des Armées, Clamart, France
| | - Mélanie Dandrieux
- Service de Neurologie, Hôpital d'Instruction des Armées Percy, Service de Santé des Armées, Clamart, France
| | - Eva Legendre
- Service de Neurologie, Hôpital d'Instruction des Armées Percy, Service de Santé des Armées, Clamart, France
| | - Pierre Paul Vidal
- COGNAC-G (UMR 8257), CNRS Service de Santé des Armées, University Paris Descartes, Paris, France.,Hangzhou Dianzi University, Zhejiang, China
| | - Damien Ricard
- COGNAC-G (UMR 8257), CNRS Service de Santé des Armées, University Paris Descartes, Paris, France.,Service de Neurologie, Hôpital d'Instruction des Armées Percy, Service de Santé des Armées, Clamart, France.,École du Val-de-Grâce, Ecole de Santé des Armées, Paris, France
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6
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Dot T, Quijoux F, Oudre L, Vienne-Jumeau A, Moreau A, Vidal PP, Ricard D. Non-Linear Template-Based Approach for the Study of Locomotion. SENSORS 2020; 20:s20071939. [PMID: 32235667 PMCID: PMC7180476 DOI: 10.3390/s20071939] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 03/17/2020] [Accepted: 03/26/2020] [Indexed: 12/25/2022]
Abstract
The automatic detection of gait events (i.e., Initial Contact (IC) and Final Contact (FC)) is crucial for the characterisation of gait from Inertial Measurements Units. In this article, we present a method for detecting steps (i.e., IC and FC) from signals of gait sequences of individuals recorded with a gyrometer. The proposed approach combines the use of a dictionary of templates and a Dynamic Time Warping (DTW) measure of fit to retrieve these templates into input signals. Several strategies for choosing and learning the adequate templates from annotated data are also described. The method is tested on thirteen healthy subjects and compared to gold standard. Depending of the template choice, the proposed algorithm achieves average errors from 0.01 to 0.03 s for the detection of IC, FC and step duration. Results demonstrate that the use of DTW allows achieving these performances with only one single template. DTW is a convenient tool to perform pattern recognition on gait gyrometer signals. This study paves the way for new step detection methods: it shows that using one single template associated with non-linear deformations may be sufficient to model the gait of healthy subjects.
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Affiliation(s)
- Tristan Dot
- Université Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France
- Université de Paris, CNRS, Centre Borelli, F-75005 Paris, France
| | - Flavien Quijoux
- Université Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France
- Université de Paris, CNRS, Centre Borelli, F-75005 Paris, France
- ORPEA Group, F-92813 Puteaux, France
| | - Laurent Oudre
- Université Sorbonne Paris Nord, L2TI, UR 3043, F-93430 Villetaneuse, France
- Correspondence: ; Tel.: +33-1-49-40-40-63
| | - Aliénor Vienne-Jumeau
- Université Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France
- Université de Paris, CNRS, Centre Borelli, F-75005 Paris, France
| | - Albane Moreau
- Université Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France
- Université de Paris, CNRS, Centre Borelli, F-75005 Paris, France
- Service de Neurologie, Service de Santé des Armées, Hôpital d’Instruction des Armées Percy, F-92190 Clamart, France
| | - Pierre-Paul Vidal
- Université Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France
- Université de Paris, CNRS, Centre Borelli, F-75005 Paris, France
- Hangzhou Dianzi University, Hangzhou C-310005, China
| | - Damien Ricard
- Université Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France
- Université de Paris, CNRS, Centre Borelli, F-75005 Paris, France
- Service de Neurologie, Service de Santé des Armées, Hôpital d’Instruction des Armées Percy, F-92190 Clamart, France
- Ecole du Val-de-Grâce, Ecole de Santé des Armées, F-75005 Paris, France
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7
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Vienne-Jumeau A, Oudre L, Moreau A, Quijoux F, Vidal PP, Ricard D. Comparing Gait Trials with Greedy Template Matching. SENSORS 2019; 19:s19143089. [PMID: 31336957 PMCID: PMC6679258 DOI: 10.3390/s19143089] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 07/09/2019] [Accepted: 07/11/2019] [Indexed: 01/15/2023]
Abstract
Gait assessment and quantification have received an increased interest in recent years. Embedded technologies and low-cost sensors can be used for the longitudinal follow-up of various populations (neurological diseases, elderly, etc.). However, the comparison of two gait trials remains a tricky question as standard gait features may prove to be insufficient in some cases. This article describes a new algorithm for comparing two gait trials recorded with inertial measurement units (IMUs). This algorithm uses a library of step templates extracted from one trial and attempts to detect similar steps in the second trial through a greedy template matching approach. The output of our method is a similarity index (SId) comprised between 0 and 1 that reflects the similarity between the patterns observed in both trials. Results on healthy and multiple sclerosis subjects show that this new comparison tool can be used for both inter-individual comparison and longitudinal follow-up.
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Affiliation(s)
- Aliénor Vienne-Jumeau
- COGNAC-G (UMR 8257), CNRS Service de Santé des Armées University Paris Descartes, 75006 Paris, France
| | - Laurent Oudre
- COGNAC-G (UMR 8257), CNRS Service de Santé des Armées University Paris Descartes, 75006 Paris, France.
- L2TI, University Paris 13, 93430 Villetaneuse, France.
- CMLA (UMR 8536), CNRS ENS Paris-Saclay, 94235 Cachan, France.
| | - Albane Moreau
- COGNAC-G (UMR 8257), CNRS Service de Santé des Armées University Paris Descartes, 75006 Paris, France
| | - Flavien Quijoux
- COGNAC-G (UMR 8257), CNRS Service de Santé des Armées University Paris Descartes, 75006 Paris, France
- ORPEA Group, 92813 Puteaux, France
| | - Pierre-Paul Vidal
- COGNAC-G (UMR 8257), CNRS Service de Santé des Armées University Paris Descartes, 75006 Paris, France
- Hangzhou Dianzi University, 310005 Hangzhou, China
| | - Damien Ricard
- COGNAC-G (UMR 8257), CNRS Service de Santé des Armées University Paris Descartes, 75006 Paris, France
- Service de Neurologie, Hôpital d'Instruction des Armées Percy, Service de Santé des Armées, 92190 Clamart, France
- Ecole du Val-de-Grâce, Ecole de Santé des Armées, 75005 Paris, France
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8
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Panhwar YN, Naghdy F, Naghdy G, Stirling D, Potter J. Assessment of frailty: a survey of quantitative and clinical methods. BMC Biomed Eng 2019; 1:7. [PMID: 32903310 PMCID: PMC7422496 DOI: 10.1186/s42490-019-0007-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Accepted: 02/25/2019] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Frailty assessment is a critical approach in assessing the health status of older people. The clinical tools deployed by geriatricians to assess frailty can be grouped into two categories; using a questionnaire-based method or analyzing the physical performance of the subject. In performance analysis, the time taken by a subject to complete a physical task such as walking over a specific distance, typically three meters, is measured. The questionnaire-based method is subjective, and the time-based performance analysis does not necessarily identify the kinematic characteristics of motion and their root causes. However, kinematic characteristics are crucial in measuring the degree of frailty. RESULTS The studies reviewed in this paper indicate that the quantitative analysis of activity of daily living, balance and gait are significant methods for assessing frailty in older people. Kinematic parameters (such as gait speed) and sensor-derived parameters are also strong markers of frailty. Seventeen gait parameters are found to be sensitive for discriminating various frailty levels. Gait velocity is the most significant parameter. Short term monitoring of daily activities is a more significant method for frailty assessment than is long term monitoring and can be implemented easily using clinical tests such as sit to stand or stand to sit. The risk of fall can be considered an outcome of frailty. CONCLUSION Frailty is a multi-dimensional phenomenon that is defined by various domains; physical, social, psychological and environmental. The physical domain has proven to be essential in the objective determination of the degree of frailty in older people. The deployment of inertial sensor in clinical tests is an effective method for the objective assessment of frailty.
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Affiliation(s)
| | | | | | | | - Janette Potter
- University of Wollongong, Wollongong, Australia
- Illawarra Health and Medical Research Institute, Wollongong, Australia
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9
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Template-Based Step Detection with Inertial Measurement Units. SENSORS 2018; 18:s18114033. [PMID: 30463240 PMCID: PMC6263402 DOI: 10.3390/s18114033] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Revised: 11/07/2018] [Accepted: 11/16/2018] [Indexed: 11/16/2022]
Abstract
This article presents a method for step detection from accelerometer and gyrometer signals recorded with Inertial Measurement Units (IMUs). The principle of our step detection algorithm is to recognize the start and end times of the steps in the signal thanks to a predefined library of templates. The algorithm is tested on a database of 1020 recordings, composed of healthy subjects and patients with various neurological or orthopedic troubles. Simulations on more than 40,000 steps show that the template-based method achieves remarkable results with a 98% recall and a 98% precision. The method adapts well to pathological subjects and can be used in a medical context for robust step estimation and gait characterization.
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10
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Rhudy MB, Mahoney JM. A comprehensive comparison of simple step counting techniques using wrist- and ankle-mounted accelerometer and gyroscope signals. J Med Eng Technol 2018; 42:236-243. [PMID: 29846134 DOI: 10.1080/03091902.2018.1470692] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
The goal of this work is to compare the differences between various step counting algorithms using both accelerometer and gyroscope measurements from wrist and ankle-mounted sensors. Participants completed four different conditions on a treadmill while wearing an accelerometer and gyroscope on the wrist and the ankle. Three different step counting techniques were applied to the data from each sensor type and mounting location. It was determined that using gyroscope measurements allowed for better performance than the typically used accelerometers, and that ankle-mounted sensors provided better performance than those mounted on the wrist.
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Affiliation(s)
- Matthew B Rhudy
- a Division of Engineering , Pennsylvania State University , Reading , PA , USA
| | - Joseph M Mahoney
- a Division of Engineering , Pennsylvania State University , Reading , PA , USA
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11
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Abstract
We introduce WeAllWalk, a dataset of inertial sensor time series collected from blind and sighted walkers using a long cane or a guide dog. Ten blind volunteers (seven using a long cane, one using a guide dog, and two alternating use of a long cane and of a guide dog) as well as five sighted volunteers contributed to the data collection. The participants walked through fairly long and complex indoor routes that included obstacles to be avoided and doors to be opened. Inertial data were recorded by two iPhone 6s carried by our participants in their pockets and carefully annotated. Ground-truth heel strike times were measured by two small inertial sensor units clipped to the participants’ shoes. We also present an in-depth comparative analysis of various step counting and turn detection algorithms as tested on WeAllWalk. This analysis reveals interesting differences between the achievable accuracy of step and turn detection across different communities of sighted and blind walkers.
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12
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Quantitative Analysis of Motor Status in Parkinson's Disease Using Wearable Devices: From Methodological Considerations to Problems in Clinical Applications. PARKINSONS DISEASE 2017; 2017:6139716. [PMID: 28607801 PMCID: PMC5451764 DOI: 10.1155/2017/6139716] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Revised: 03/23/2017] [Accepted: 04/27/2017] [Indexed: 11/17/2022]
Abstract
Long-term and objective monitoring is necessary for full assessment of the condition of patients with Parkinson's disease (PD). Recent advances in biotechnology have seen the development of various types of wearable (body-worn) sensor systems. By using accelerometers and gyroscopes, these devices can quantify motor abnormalities, including decreased activity and gait disturbances, as well as nonmotor signs, such as sleep disturbances and autonomic dysfunctions in PD. This review discusses methodological problems inherent in wearable devices. Until now, analysis of the mean values of motion-induced signals on a particular day has been widely applied in the clinical management of PD patients. On the other hand, the reliability of these devices to detect various events, such as freezing of gait and dyskinesia, has been less than satisfactory. Quantification of disease-specific changes rather than nonspecific changes is necessary.
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Beltrame T, Hughson RL. Aerobic system analysis based on oxygen uptake and hip acceleration during random over-ground walking activities. Am J Physiol Regul Integr Comp Physiol 2016; 312:R93-R100. [PMID: 27856415 DOI: 10.1152/ajpregu.00381.2016] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 11/14/2016] [Accepted: 11/14/2016] [Indexed: 11/22/2022]
Abstract
Deteriorated aerobic response to moderate exercise might precede the manifestation of clinical symptoms of noncommunicable diseases. The purpose of the current study was to verify that the use of current wearable technologies for analysis of pulmonary oxygen uptake (V̇o2) dynamics during a pseudorandom ternary sequence (PRTS) over-ground walking protocol is a suitable procedure for the investigation of the aerobic response in more realistic settings. A wearable accelerometer located at the hip assessed the magnitude of the input changes delivered to the aerobic system. Eight adults (24 ± 4 yr old, 174 ± 7 cm, and 71.4 ± 7.4 kg) performed two identical PRTS over-ground walking protocols. In addition, they performed on the cycle ergometer two identical pseudorandom binary sequence (PRBS) protocols and one incremental protocol for maximal V̇o2 determination. In the frequency domain, mean normalized gain amplitude (MNG in %) quantified V̇o2 dynamics. The MNG during PRTS was correlated (r = -0.80, P = 0.01) with the V̇o2 time constant (τ) obtained during cycling. The MNG estimated during PRBS was similar to the MNG estimated during PRTS (r = 0.80, P = 0.01). The maximal V̇o2 correlated with the MNG obtained during the PRBS (r = 0.79, P = 0.01) and PRTS (r = 0.78, P = 0.02) protocols. In conclusion, PRTS over-ground walking protocol can be used to evaluate the aerobic system dynamics by the simultaneous measurement of V̇o2 and hip acceleration. In addition, the aerobic response dynamics from PRBS and PRTS were correlated to maximal V̇o2 This study has shown that wearable technologies in combination with assessment of MNG, a novel indicator of system dynamics, open new possibilities to monitor cardiorespiratory health under conditions that better simulate activities of daily living than cardiopulmonary exercise testing performed in a medical environment.
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Affiliation(s)
- Thomas Beltrame
- Faculty of Applied Health Sciences, University of Waterloo, Waterloo, Ontario, Canada; and.,Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brasília, Distrito Federal, Brazil
| | - Richard L Hughson
- Faculty of Applied Health Sciences, University of Waterloo, Waterloo, Ontario, Canada; and
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Barrois R, Gregory T, Oudre L, Moreau T, Truong C, Aram Pulini A, Vienne A, Labourdette C, Vayatis N, Buffat S, Yelnik A, de Waele C, Laporte S, Vidal PP, Ricard D. An Automated Recording Method in Clinical Consultation to Rate the Limp in Lower Limb Osteoarthritis. PLoS One 2016; 11:e0164975. [PMID: 27776168 PMCID: PMC5077168 DOI: 10.1371/journal.pone.0164975] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2015] [Accepted: 10/04/2016] [Indexed: 11/19/2022] Open
Abstract
For diagnosis and follow up, it is important to be able to quantify limp in an objective, and precise way adapted to daily clinical consultation. The purpose of this exploratory study was to determine if an inertial sensor-based method could provide simple features that correlate with the severity of lower limb osteoarthritis evaluated by the WOMAC index without the use of step detection in the signal processing. Forty-eight patients with lower limb osteoarthritis formed two severity groups separated by the median of the WOMAC index (G1, G2). Twelve asymptomatic age-matched control subjects formed the control group (G0). Subjects were asked to walk straight 10 meters forward and 10 meters back at self-selected walking speeds with inertial measurement units (IMU) (3-D accelerometers, 3-D gyroscopes and 3-D magnetometers) attached on the head, the lower back (L3-L4) and both feet. Sixty parameters corresponding to the mean and the root mean square (RMS) of the recorded signals on the various sensors (head, lower back and feet), in the various axes, in the various frames were computed. Parameters were defined as discriminating when they showed statistical differences between the three groups. In total, four parameters were found discriminating: mean and RMS of the norm of the acceleration in the horizontal plane for contralateral and ipsilateral foot in the doctor's office frame. No discriminating parameter was found on the head or the lower back. No discriminating parameter was found in the sensor linked frames. This study showed that two IMUs placed on both feet and a step detection free signal processing method could be an objective and quantitative complement to the clinical examination of the physician in everyday practice. Our method provides new automatically computed parameters that could be used for the comprehension of lower limb osteoarthritis. It may not only be used in medical consultation to score patients but also to monitor the evolution of their clinical syndrome during and after rehabilitation. Finally, it paves the way for the quantification of gait in other fields such as neurology and for monitoring the gait at a patient's home.
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Affiliation(s)
- R. Barrois
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
| | - Th. Gregory
- Service de chirurgie orthopédique et traumatologie, HEGP, université Paris Descartes, Paris, France
| | - L. Oudre
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
- Institut Galilée, Université Paris 13, Villetaneuse, France
| | - Th. Moreau
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
| | - Ch. Truong
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
| | - A. Aram Pulini
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
| | - A. Vienne
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
| | - Ch. Labourdette
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
- Centre des Mathématiques et de Leurs Applications, Ecole Normale Supérieure de Cachan, Cachan, France
| | - N. Vayatis
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
- Centre des Mathématiques et de Leurs Applications, Ecole Normale Supérieure de Cachan, Cachan, France
| | - S. Buffat
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
- Institut de Recherche Biomédicale des Armées, Brétigny-sur-Orge, France
| | - A. Yelnik
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
- PRM Department, GH St Louis Lariboisière F. Widal, AP-HP, Diderot University, Paris, France
| | - C. de Waele
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
| | - S. Laporte
- LBM/Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers Paris Tech, 151 Boulevard de l’Hôpital, 75003, Paris, France
| | - P. P. Vidal
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
| | - D. Ricard
- Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France
- Service de Neurologie, Hôpital d’Instruction des Armées de Percy, Service de Santé des Armées, Clamart, France
- * E-mail:
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Capela NA, Lemaire ED, Baddour NC. A smartphone approach for the 2 and 6-minute walk test. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2016; 2014:958-61. [PMID: 25570119 DOI: 10.1109/embc.2014.6943751] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The 2 and 6-minute walk tests (2-6MWT) are used by rehabilitation professionals as a measure of exercise capacity. Our research has produced a new 2-6MWT BlackBerry smartphone application (app) that can be used to run the 2-6MWT and also provide new information about how the person moves during the test. The smartphone is worn on a belt at the lower back to record phone sensor data while walking. This data is used to identify foot strikes, calculate the total distance walked and step timing, and analyze pelvis accelerations. Information on symmetry, walking changes over time, and poor walking patterns is not available from a typical 2-6MWT and could help with clinical decision-making. The 2-6MWT app was evaluated in a pilot test using data from five able-bodied participants. Foot strike time was within 0.07 seconds when compared to gold standard video recordings. The total distance calculated by the app was within 1m of the measured distance.
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Ehrler F, Weber C, Lovis C. Influence of Pedometer Position on Pedometer Accuracy at Various Walking Speeds: A Comparative Study. J Med Internet Res 2016; 18:e268. [PMID: 27713114 PMCID: PMC5073206 DOI: 10.2196/jmir.5916] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Revised: 08/20/2016] [Accepted: 09/14/2016] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Demographic growth in conjunction with the rise of chronic diseases is increasing the pressure on health care systems in most OECD countries. Physical activity is known to be an essential factor in improving or maintaining good health. Walking is especially recommended, as it is an activity that can easily be performed by most people without constraints. Pedometers have been extensively used as an incentive to motivate people to become more active. However, a recognized problem with these devices is their diminishing accuracy associated with decreased walking speed. The arrival on the consumer market of new devices, worn indifferently either at the waist, wrist, or as a necklace, gives rise to new questions regarding their accuracy at these different positions. OBJECTIVE Our objective was to assess the performance of 4 pedometers (iHealth activity monitor, Withings Pulse O2, Misfit Shine, and Garmin vívofit) and compare their accuracy according to their position worn, and at various walking speeds. METHODS We conducted this study in a controlled environment with 21 healthy adults required to walk 100 m at 3 different paces (0.4 m/s, 0.6 m/s, and 0.8 m/s) regulated by means of a string attached between their legs at the level of their ankles and a metronome ticking the cadence. To obtain baseline values, we asked the participants to walk 200 m at their own pace. RESULTS A decrease of accuracy was positively correlated with reduced speed for all pedometers (12% mean error at self-selected pace, 27% mean error at 0.8 m/s, 52% mean error at 0.6 m/s, and 76% mean error at 0.4 m/s). Although the position of the pedometer on the person did not significantly influence its accuracy, some interesting tendencies can be highlighted in 2 settings: (1) positioning the pedometer at the waist at a speed greater than 0.8 m/s or as a necklace at preferred speed tended to produce lower mean errors than at the wrist position; and (2) at a slow speed (0.4 m/s), pedometers worn at the wrist tended to produce a lower mean error than in the other positions. CONCLUSIONS At all positions, all tested pedometers generated significant errors at slow speeds and therefore cannot be used reliably to evaluate the amount of physical activity for people walking slower than 0.6 m/s (2.16 km/h, or 1.24 mph). At slow speeds, the better accuracy observed with pedometers worn at the wrist could constitute a valuable line of inquiry for the future development of devices adapted to elderly people.
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Affiliation(s)
- Frederic Ehrler
- Division of Medical Information Sciences, University Hospitals of Geneva, Geneva, Switzerland.
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Dasenbrock L, Heinks A, Schwenk M, Bauer JM. Technology-based measurements for screening, monitoring and preventing frailty. Z Gerontol Geriatr 2016; 49:581-595. [DOI: 10.1007/s00391-016-1129-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Revised: 08/09/2016] [Accepted: 08/15/2016] [Indexed: 10/21/2022]
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Soaz C, Diepold K. Step Detection and Parameterization for Gait Assessment Using a Single Waist-Worn Accelerometer. IEEE Trans Biomed Eng 2016; 63:933-942. [DOI: 10.1109/tbme.2015.2480296] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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19
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Accuracy of a custom physical activity and knee angle measurement sensor system for patients with neuromuscular disorders and gait abnormalities. SENSORS 2015; 15:10734-52. [PMID: 25954954 PMCID: PMC4482003 DOI: 10.3390/s150510734] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Revised: 04/15/2015] [Accepted: 04/30/2015] [Indexed: 11/24/2022]
Abstract
Long-term assessment of ambulatory behavior and joint motion are valuable tools for the evaluation of therapy effectiveness in patients with neuromuscular disorders and gait abnormalities. Even though there are several tools available to quantify ambulatory behavior in a home environment, reliable measurement of joint motion is still limited to laboratory tests. The aim of this study was to develop and evaluate a novel inertial sensor system for ambulatory behavior and joint motion measurement in the everyday environment. An algorithm for behavior classification, step detection, and knee angle calculation was developed. The validation protocol consisted of simulated daily activities in a laboratory environment. The tests were performed with ten healthy subjects and eleven patients with multiple sclerosis. Activity classification showed comparable performance to commercially available activPAL sensors. Step detection with our sensor system was more accurate. The calculated flexion-extension angle of the knee joint showed a root mean square error of less than 5° compared with results obtained using an electro-mechanical goniometer. This new system combines ambulatory behavior assessment and knee angle measurement for long-term measurement periods in a home environment. The wearable sensor system demonstrated high validity for behavior classification and knee joint angle measurement in a laboratory setting.
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Ahanathapillai V, Amor JD, Goodwin Z, James CJ. Preliminary study on activity monitoring using an android smart-watch. Healthc Technol Lett 2015; 2:34-9. [PMID: 26609402 PMCID: PMC4611205 DOI: 10.1049/htl.2014.0091] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Revised: 01/19/2015] [Accepted: 01/20/2015] [Indexed: 11/22/2022] Open
Abstract
The global trend for increasing life expectancy is resulting in aging populations in a number of countries. This brings to bear a pressure to provide effective care for the older population with increasing constraints on available resources. Providing care for and maintaining the independence of an older person in their own home is one way that this problem can be addressed. The EU Funded Unobtrusive Smart Environments for Independent Living (USEFIL) project is an assistive technology tool being developed to enhance independent living. As part of USEFIL, a wrist wearable unit (WWU) is being developed to monitor the physical activity (PA) of the user and integrate with the USEFIL system. The WWU is a novel application of an existing technology to the assisted living problem domain. It combines existing technologies and new algorithms to extract PA parameters for activity monitoring. The parameters that are extracted include: activity level, step count and worn state. The WWU, the algorithms that have been developed and a preliminary validation are presented. The results show that activity level can be successfully extracted, that worn state can be correctly identified and that step counts in walking data can be estimated within 3% error, using the controlled dataset.
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Affiliation(s)
- Vijayalakshmi Ahanathapillai
- International Digital Laboratory , Institute of Digital Healthcare - WMG , University of Warwick , Coventry , CV4 7AL , UK
| | - James D Amor
- Warwick Engineering in Biomedicine , School of Engineering , University of Warwick , Coventry , CV4 7AL , UK
| | - Zoe Goodwin
- Management Science Department , University of Strathclyde , Glasgow , G1 1XQ , UK
| | - Christopher J James
- Warwick Engineering in Biomedicine , School of Engineering , University of Warwick , Coventry , CV4 7AL , UK
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Novel algorithm for a smartphone-based 6-minute walk test application: algorithm, application development, and evaluation. J Neuroeng Rehabil 2015; 12:19. [PMID: 25889112 PMCID: PMC4343050 DOI: 10.1186/s12984-015-0013-9] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2014] [Accepted: 02/11/2015] [Indexed: 11/14/2022] Open
Abstract
Background The 6-minute walk test (6MWT: the maximum distance walked in 6 minutes) is used by rehabilitation professionals as a measure of exercise capacity. Today’s smartphones contain hardware that can be used for wearable sensor applications and mobile data analysis. A smartphone application can run the 6MWT and provide typically unavailable biomechanical information about how the person moves during the test. Methods A new algorithm for a calibration-free 6MWT smartphone application was developed that uses the test’s inherent conditions and smartphone accelerometer-gyroscope data to report the total distance walked, step timing, gait symmetry, and walking changes over time. This information is not available with a standard 6MWT and could help with clinical decision-making. The 6MWT application was evaluated with 15 able-bodied participants. A BlackBerry Z10 smartphone was worn on a belt at the mid lower back. Audio from the phone instructed the person to start and stop walking. Digital video was independently recorded during the trial as a gold-standard comparator. Results The average difference between smartphone and gold standard foot strike timing was 0.014 ± 0.015 s. The total distance calculated by the application was within 1 m of the measured distance for all but one participant, which was more accurate than other smartphone-based studies. Conclusions These results demonstrated that clinically relevant 6MWT results can be achieved with typical smartphone hardware and a novel algorithm. Electronic supplementary material The online version of this article (doi:10.1186/s12984-015-0013-9) contains supplementary material, which is available to authorized users.
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Calliess T, Bocklage R, Karkosch R, Marschollek M, Windhagen H, Schulze M. Clinical evaluation of a mobile sensor-based gait analysis method for outcome measurement after knee arthroplasty. SENSORS 2014; 14:15953-64. [PMID: 25171119 PMCID: PMC4208155 DOI: 10.3390/s140915953] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2013] [Revised: 07/28/2014] [Accepted: 08/22/2014] [Indexed: 11/16/2022]
Abstract
Clinical scores and motion-capturing gait analysis are today's gold standard for outcome measurement after knee arthroplasty, although they are criticized for bias and their ability to reflect patients' actual quality of life has been questioned. In this context, mobile gait analysis systems have been introduced to overcome some of these limitations. This study used a previously developed mobile gait analysis system comprising three inertial sensor units to evaluate daily activities and sports. The sensors were taped to the lumbosacral junction and the thigh and shank of the affected limb. The annotated raw data was evaluated using our validated proprietary software. Six patients undergoing knee arthroplasty were examined the day before and 12 months after surgery. All patients reported a satisfactory outcome, although four patients still had limitations in their desired activities. In this context, feasible running speed demonstrated a good correlation with reported impairments in sports-related activities. Notably, knee flexion angle while descending stairs and the ability to stop abruptly when running exhibited good correlation with the clinical stability and proprioception of the knee. Moreover, fatigue effects were displayed in some patients. The introduced system appears to be suitable for outcome measurement after knee arthroplasty and has the potential to overcome some of the limitations of stationary gait labs while gathering additional meaningful parameters regarding the force limits of the knee.
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Affiliation(s)
- Tilman Calliess
- Department for Orthopaedic Surgery at the Annastift, Hannover Medical School, 30625 Hannover, Germany.
| | - Raphael Bocklage
- Department for Orthopaedic Surgery at the Annastift, Hannover Medical School, 30625 Hannover, Germany.
| | - Roman Karkosch
- Department for Orthopaedic Surgery at the Annastift, Hannover Medical School, 30625 Hannover, Germany.
| | - Michael Marschollek
- Hannover Medical School, Peter L. Reichertz Institute for Medical Informatics, University of Braunschweig-Institute of Technology and Hannover Medical School, 30625 Hannover, Germany.
| | - Henning Windhagen
- Department for Orthopaedic Surgery at the Annastift, Hannover Medical School, 30625 Hannover, Germany.
| | - Mareike Schulze
- Hannover Medical School, Peter L. Reichertz Institute for Medical Informatics, University of Braunschweig-Institute of Technology and Hannover Medical School, 30625 Hannover, Germany.
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Lambiase MJ, Gabriel KP, Kuller LH, Matthews KA. Temporal relationships between physical activity and sleep in older women. Med Sci Sports Exerc 2014; 45:2362-8. [PMID: 23739529 DOI: 10.1249/mss.0b013e31829e4cea] [Citation(s) in RCA: 76] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
PURPOSE The objective of this study is to examine the temporal and bidirectional relationships between accelerometer-derived physical activity estimates and actigraphy-assessed sleep characteristics among older women. METHODS A subgroup of participants (N = 143, mean age = 73 yr) enrolled in the Healthy Women Study wore an ActiGraph accelerometer on their waist and an Actiwatch sleep monitor on their wrist concurrently for seven consecutive days. Multilevel models examined whether ActiGraph-assessed daily activity counts (ct·min⁻¹·d⁻¹) and moderate- to vigorous-intensity physical activity (MVPA; min·d⁻¹) predicted Actiwatch-assessed sleep onset latency, total sleep time, sleep efficiency, and sleep fragmentation. Similar models were used to determine whether nighttime sleep characteristics predicted physical activity the following day. RESULTS In unadjusted models, greater daily activity counts (B = -0.05, P = 0.005) and more minutes of MVPA (B = -0.03, P = 0.01) were temporally associated with less total sleep time across the week. Greater sleep efficiency was associated with greater daily activity counts (B = 0.37, P = 0.01) and more minutes of MVPA (B = 0.64, P = 0.009) the following day. Less sleep fragmentation was also associated with greater daily activity counts and more MVPA the following day. Findings were similar after adjustment for age, education, body mass index, depressive symptoms, arthritis, and accelerometer wear time. CONCLUSIONS Few studies have used objective measures to examine the temporal relationships between physical activity and sleep. Notably, these findings suggest that nightly variations in sleep efficiency influence physical activity the following day. Thus, improving overall sleep quality in addition to reducing nightly fluctuations in sleep may be important for encouraging a physically active lifestyle in older women.
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Affiliation(s)
- Maya J Lambiase
- 1Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA; 2Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Austin, TX; and 3Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA
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Yoneyama M, Kurihara Y, Watanabe K, Mitoma H. Accelerometry-Based Gait Analysis and Its Application to Parkinson's Disease Assessment— Part 1: Detection of Stride Event. IEEE Trans Neural Syst Rehabil Eng 2014; 22:613-22. [DOI: 10.1109/tnsre.2013.2260561] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Samà A, Ruiz FJ, Agell N, Pérez-López C, Català A, Cabestany J. Gait identification by means of box approximation geometry of reconstructed attractors in latent space. Neurocomputing 2013. [DOI: 10.1016/j.neucom.2012.12.042] [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]
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Gietzelt M, Wolf KH, Kohlmann M, Marschollek M, Haux R. Measurement of accelerometry-based gait parameters in people with and without dementia in the field: a technical feasibility study. Methods Inf Med 2013; 52:319-25. [PMID: 23807731 DOI: 10.3414/me12-02-0009] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2012] [Accepted: 04/09/2013] [Indexed: 11/09/2022]
Abstract
BACKGROUND Gait analyses are an important tool to diagnose diseases or to measure the rehabilitation process of patients. In this context, sensor-based systems, and especially accelerometers, gain in importance. They are able to improve objectiveness of gait analyses. In clinical settings, there is usually a supervisor who gives instructions to the patients, but this can have an influence on patients' gait. It is expected that this effect will be smaller in field studies. OBJECTIVE Aim of this study was to capture and evaluate gait parameters measured by a single waist-mounted accelerometer during everyday life of subjects. METHODS Due to missing ground-truth in unsupervised conditions, another external criterion had to be chosen. Subjects of two different groups were considered: patients with dementia (DEM) and active older people (ACT). These groups were chosen, because of the expected difference in gait. The idea was to quantify the expected difference of accelerometric-based gait parameters. Gait parameters were e.g. velocity, step frequency, compensation movements, and variance of the accelerometric signal. RESULTS Ten subjects were measured in each group. The number of walking episodes captured was 1,187 (DEM) vs. 1,809 (ACT). The compensation and variance parameters showed an AUC value (Area Under the Curve) between 0.88 and 0.92. In contrast, velocity and step frequency performed poorly (AUC values of 0.51 and 0.55). It was possible to classify both groups using these parameters with an accuracy of 89.2%. CONCLUSION The results showed a much higher amount of walking episodes in field studies compared to supervised clinical trials. The classification showed a high accuracy in distinguishing between both groups.
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Affiliation(s)
- M Gietzelt
- Peter L. Reichertz Institute for Medical Informatics, University of Braunschweig – Institute of Technology and Hanover Medical School, Braunschweig, Germany.
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Gietzelt M, Spehr J, Ehmen Y, Wegel S, Feldwieser F, Meis M, Marschollek M, Wolf KH, Steinhagen-Thiessen E, Gövercin M. GAL@Home: a feasibility study of sensor-based in-home fall detection. Z Gerontol Geriatr 2013. [PMID: 23184297 DOI: 10.1007/s00391-012-0400-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
BACKGROUND A considerable proportion of falls occur within the domestic environment. Sensor-based identification of falls in seniors' homes could help them to remain autonomous and self-sufficient in their own homes. The objective of this study was to evaluate fall detection systems within the home environment using optical and accelerometric sensor systems. METHODS Portable triaxial accelerometers and optical sensors were used to detect falls in subjects with known problems of mobility and a recent fall history. RESULTS Three subjects were investigated with the system. Overall nine falls occurred during the study period. Four falls were recorded by the accelerometric system and one fall by the optical system. Subjects with increased risk of falling as measured with mobility and fall risk assessments tend to fall more frequently. CONCLUSION The study shows that there is a considerably large difference between fall-detector evaluation studies in domestic environments and in laboratory trials.
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Affiliation(s)
- M Gietzelt
- University of Braunschweig-Institute of Technology and Hannover Medical School, Mühlenpfordtstr. 23, 38106, Braunschweig, Germany.
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Marschollek M, Gietzelt M, Schulze M, Kohlmann M, Song B, Wolf KH. Wearable sensors in healthcare and sensor-enhanced health information systems: all our tomorrows? Healthc Inform Res 2012; 18:97-104. [PMID: 22844645 PMCID: PMC3402561 DOI: 10.4258/hir.2012.18.2.97] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2012] [Revised: 06/21/2012] [Accepted: 06/21/2012] [Indexed: 11/23/2022] Open
Abstract
Wearable sensor systems which allow for remote or self-monitoring of health-related parameters are regarded as one means to alleviate the consequences of demographic change. This paper aims to summarize current research in wearable sensors as well as in sensor-enhanced health information systems. Wearable sensor technologies are already advanced in terms of their technical capabilities and are frequently used for cardio-vascular monitoring. Epidemiologic predictions suggest that neuropsychiatric diseases will have a growing impact on our health systems and thus should be addressed more intensively. Two current project examples demonstrate the benefit of wearable sensor technologies: long-term, objective measurement under daily-life, unsupervised conditions. Finally, up-to-date approaches for the implementation of sensor-enhanced health information systems are outlined. Wearable sensors are an integral part of future pervasive, ubiquitous and person-centered health care delivery. Future challenges include their integration into sensor-enhanced health information systems and sound evaluation studies involving measures of workload reduction and costs.
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Affiliation(s)
- Michael Marschollek
- Hanover Medical School, Peter L. Reichertz Institute for Medical Informatics, Hanover, Germany
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