IMU-based motion capture system for rehabilitation applications: A systematic review

Biomimetic Intelligence and Robotics, Journal Year: 2023, Volume and Issue: 3(2), P. 100097 - 100097

Published: Feb. 27, 2023

In recent years, the use of inertial measurement unit (IMU)-based motion capture (Mocap) systems in rehabilitation has grown significantly. This paper aimed to provide an overview current IMU-based Mocap system designs field rehabilitation, explore specific applications and implementation these systems, discuss potential future developments considering sensor limitations. For this review, a systematic literature search was conducted using Scopus, IEEE Xplore, PubMed, Web Science from 2013 2022. A total 65 studies were included analyzed based on their application, target population, deployment measurement. The proportion assessment, training, both 82%, 12%, 6% respectively. results showed that primary focus stroke one most commonly studied pathological disease. Additionally, general without targeting pathology also examined widely, with particular emphasis gait analysis. common configuration for analysis two IMUs measuring spatiotemporal parameters lower limb. However, lack training upper limb could be attributed limited battery life drift. To address issue, low-power chips low-consumption transmission pathways way extend usage time long-term training. Furthermore, we suggest development highly integrated multi-modal fusion.

Language: Английский

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Characterization of Walking in Mild Parkinson’s Disease: Reliability, Validity and Discriminant Ability of the Six-Minute Walk Test Instrumented with a Single Inertial Sensor

Sensors, Journal Year: 2024, Volume and Issue: 24(2), P. 662 - 662

Published: Jan. 20, 2024

Although the 6-Minute Walk Test (6MWT) is among recommended clinical tools to assess gait impairments in individuals with Parkinson’s disease (PD), its standard outcome consists only of distance walked 6 min. Integrating a single Inertial Measurement Unit (IMU) could provide additional quantitative and objective information about quality complementing outcome. This study aims evaluate test–retest reliability, validity discriminant ability parameters obtained by IMU during 6MWT subjects mild PD. Twenty-two people PD ten healthy persons performed wearing an placed on lower trunk. Features belonging rhythm pace, variability, regularity, jerkiness, intensity, dynamic instability symmetry domains were computed. Test–retest reliability was evaluated through Intraclass Correlation Coefficient (ICC), while concurrent determined Spearman’s coefficient. Mann–Whitney U test Area Under receiver operating characteristic Curve (AUC) then applied reliable valid parameters. Results showed overall high (ICC ≥ 0.75) multiple significant correlations scales all domains. Several features exhibited alterations compared controls. Our findings suggested that instrumented can offers details possibility being integrated into evaluations better define walking rehabilitation strategies quick easy way.

Language: Английский

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Optimizing Rare Disease Gait Classification through Data Balancing and Generative AI: Insights from Hereditary Cerebellar Ataxia

Sensors, Journal Year: 2024, Volume and Issue: 24(11), P. 3613 - 3613

Published: June 3, 2024

The interpretability of gait analysis studies in people with rare diseases, such as those primary hereditary cerebellar ataxia (pwCA), is frequently limited by the small sample sizes and unbalanced datasets. purpose this study was to assess effectiveness data balancing generative artificial intelligence (AI) algorithms generating synthetic reflecting actual abnormalities pwCA. Gait 30 pwCA (age: 51.6 ± 12.2 years; 13 females, 17 males) 100 healthy subjects 57.1 10.4; 60 40 were collected at lumbar level an inertial measurement unit. Subsampling, oversampling, minority adversarial networks, conditional tabular networks (ctGAN) applied generate datasets be input a random forest classifier. Consistency explainability metrics also calculated coherence generated dataset known ctGAN significantly improved classification performance compared original traditional augmentation methods. are effective methods for from populations owing their ability improve diagnostic models consistent explainability.

Language: Английский

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Mapping Trajectories of Gait Recovery in Clinical Stroke Rehabilitation

Neurorehabilitation and neural repair, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 14, 2025

Background How gait changes during the early stages of stoke rehabilitation, and which patient characteristics are associated with these is still largely unknown. Objective he first objective was to describe in stroke rehabilitation. Secondly, we determined how various were rate change over time. Methods Participants measured every 3 weeks The assessment consisted an inertial measurement unit (IMU) based 2-minute walk test (2MWT), IMU-based balance tests, standard clinical tests. In 2MWT, participants equipped IMUs, from speed, variability, asymmetry, smoothness calculated. examined admission discharge at individual level. effect on features time assessed growth models. Results A total 81 Trajectories 72 analyzed. On basis, speed increased 32 trajectories. Only a few trajectories exhibited significant rehabilitation period. models revealed increase decrease variability smoothness. Berg Balance Scale onset (negatively) rates smoothness, respectively. Conclusion We found substantial gait-feature outcomes their progression individuals after studied had limited associations

Language: Английский

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A MACHINE LEARNING APPROACH TO REAL-TIME CALCULATION OF JOINT ANGLES DURING WALKING AND RUNNING USING SELF-PLACED INERTIAL MEASUREMENT UNITS

Gait & Posture, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

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Monitoring of child-specific activities in ambulatory children with and without developmental disabilities

BMC Pediatrics, Journal Year: 2025, Volume and Issue: 25(1)

Published: March 15, 2025

Pediatric healthcare professionals facilitate children to enhance and maintain a physically active lifestyle. Activity monitors (AM) can help pediatric assess physical activity in everyday life. However, validation research of has often been conducted laboratories insight into their own environment is lacking. Our goal was study the criterion validity prototype AM (AM-p) model natural setting. Cross-sectional community-based with ambulatory (2-19 years) without developmental disability. Children wore AM-p on ankle were filmed (gold standard) while performing an protocol We labelled all videos per 5-second epoch individual labels. Raw data synchronized Using machine learning techniques, labels subdivided three pre-defined categories. Accuracy, recall, precision, F1 score calculated category. analyzed 93 children, which 28 had Mean age 11 years (SD 4.5) 55% girls. The differentiated between 'stationary', 'cycling' 'locomotion' activities accuracy 82%, recall 78%, precision 75%, respectively. older than 13 typical development be assessed more accurately younger (2-12 disabilities. single ankle-worn differentiate categories disabilities good (82%). Because used for heterogenous group disabilities, it may support clinical assessment future.

Language: Английский

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An open-source, externally validated neural network algorithm to recognize daily-life gait of older adults based on the lower-back sensor

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 5, 2025

Abstract Background Accurate gait recognition from daily physical activities is a critical first step for further fall risk assessment and rehabilitation monitoring based on inertial sensors. However, most openly available models are healthy young adults ambulating in structured conditions. Objective This study aimed to develop an open-source externally validated algorithm daily-life of older acceleration angular velocity, as well data only, explore the effect use augmentation model training. Methods A convolutional neural network was trained recognition. The training lower-back sensor 20 (mean age 76 years old), with annotated synchronized activity labels semi-structured randomly split into training, validation, testing datasets by participants, multiple times using these different splits. six channels (accelerations velocities) three only) under conditions without augmentation, respectively. External validation evaluated collected 47 stroke survivors 72.3 old) balance walking tests. Results For dataset, median accuracy ranged 94 % 98 %, precision 63 85 sensitivity 95 97 F1-score 90 specificity %. external 100 99.9 71 83 Conclusions Based lower-back-worn data, we provide accurate, open-source, adults, one six-axis input another three-axis data. Besides, found when model, especially helpful only.

Language: Английский

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Preliminary Validation of an IMU-Based Physiotherapy Assessment System for the Lower Extremities

Pervasive Computing Technologies for Healthcare, Journal Year: 2025, Volume and Issue: unknown, P. 142 - 158

Published: Jan. 1, 2025

Language: Английский

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Reliability of IMU-based balance assessment in clinical stroke rehabilitation

Gait & Posture, Journal Year: 2022, Volume and Issue: 98, P. 62 - 68

Published: Aug. 12, 2022

Balance is often affected after stroke, severely impacting activities of daily life. Conventional testing methods to assess balance provide limited information, as they are subjected floor and ceiling effects. Instrumented tests, for instance using inertial measurement units, offer a feasible promising alternative. We examined whether postural sway can reliably be measured in sitting standing people stroke clinical rehabilitation single unit. Additionally, we assessed what extent averaging two measurements would improve test-retest reliability compared measurement, if features potentially used monitor progression. Forty participants performed assessments with interval 24 h. Each assessment consisted one four conditions (eyes open, feet together, eyes closed foam). The were twice during both assessments. In total, 35 calculated each condition. For the conditions, these average test retest measurements. determined intraclass correlation coefficient averaged minimal detectable change relative computed. resulted 22 sitting, 30 & 32 27 28 33 23 13 foam good-excellent reliability. Overall, difference between values was small inconsistent. ranged 0.5 1.5 standard deviation. Sitting

Language: Английский

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Assessment of ambulation functions through kinematic analysis in individuals with stroke: a systematic review

European Journal of Physical and Rehabilitation Medicine, Journal Year: 2025, Volume and Issue: 61(1)

Published: Feb. 1, 2025

Although kinematic assessments for stroke-induced lower limb impairments offer a promising alternative to conventional scale evaluations, interpreting high-dimensional data remains challenging due numerous metrics reported in past studies. This study aimed provide an exhaustive overview of existing studies using kinematics assess the gait individuals with stroke, along examining their clinimetric properties future clinical applications. A systematic search was conducted across PubMed (08/2024), Scopus Web Science CINAHL EMBASE and IEEE (08/2024). We included articles that recruited over 18 years old stroke utilized motion capture technologies evaluate kinematics. Similar were consolidated analysis, COSMIN Risk Bias Checklist used methodological quality investigating metrics. Convergent validity evaluated by association Fugl-Meyer limbs walking speed. Moreover, GRADE approach rate evidence. total 383 classified into 10 categories. Seven on metric reliability rated high quality. Metrics satisfactory spatiotemporal, spatial metrics, data-driven score. Six assessed convergent validity. The dynamic index, angular component coefficient correspondence (ACC), change cadence, stride length, hip range showed Among 13 studies, 12 as moderate evidence approach. There are significant variations measurements high-quality evaluating scarce. For more standardized evidence-based assessment, further research validating these assessments' is essential.

Language: Английский

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