Real-Time Monitoring for Knee Extensor Muscle Training With Flexible Sensors

Chuang, Wan-Chun; Chen, Wei-Long

doi:10.1109/jmems.2019.2941939

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…Generally, the study on human joint movements concentrated on the upper half and lower half, respectively. The shoulder joints, elbow joints, and wrist joints [30][31][32] are located on the upper half of the body, while the hip joints, knee joints, and ankle joints are located on the lower half of the body [30,[33][34][35][36]. Up to now, more research has been conducted on upper-body joint activities.…”

Section: Jointsmentioning

confidence: 99%

“…In addition, research on the upper extremity focuses on identifying limb activity. Research on joint activity focuses on the monitoring of knee joints [35,36,119], aiming to track and assess the function of the knee joint in a noninvasive manner for fall monitoring and prevention, athletic performance assessment, and rehabilitation progress observation.…”

Section: Design Of Wearable Sensor Systemsmentioning

confidence: 99%

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Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review

Huang,

Xue,

Ren

et al. 2023

Sensors

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In recent years, marked progress has been made in wearable technology for human motion and posture recognition in the areas of assisted training, medical health, VR/AR, etc. This paper systematically reviews the status quo of wearable sensing systems for human motion capture and posture recognition from three aspects, which are monitoring indicators, sensors, and system design. In particular, it summarizes the monitoring indicators closely related to human posture changes, such as trunk, joints, and limbs, and analyzes in detail the types, numbers, locations, installation methods, and advantages and disadvantages of sensors in different monitoring systems. Finally, it is concluded that future research in this area will emphasize monitoring accuracy, data security, wearing comfort, and durability. This review provides a reference for the future development of wearable sensing systems for human motion capture.

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Section: Jointsmentioning

confidence: 99%

Section: Design Of Wearable Sensor Systemsmentioning

confidence: 99%

Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review

Huang,

Xue,

Ren

et al. 2023

Sensors

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Developing an Intelligent Motor Function Assessment System (IMFAS) for post-stroke rehabilitation using multi-data fusion (Preprint)

Ye,

Tian,

Liu

et al. 2024

Preprint

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BACKGROUND Stroke remains a leading global health concern due to its high rates of incidence, recurrence, disability, mortality, and significant economic impact. Traditional methods for assessing motor function in stroke patients are often subjective and not sufficiently sensitive to subtle changes. OBJECTIVE To present the architectural, modular, and functional designs and theoretical underpinnings of a novel Intelligent Motor Function Assessment System (IMFAS) and inspire further research, development, and clinical adoptions by showcasing its design and potential applications. METHODS We developed the IMFAS through a comprehensive design process including a literature review, consultations with rehabilitation professionals, feedback from stroke patients, workflow analysis in clinical settings, and multidisciplinary input. The system incorporated several advanced technologies, including sensors, computer vision, machine learning, and virtual reality, to gather and analyze data. RESULTS The IMFAS architecture supports continuous, real-time assessment and monitoring of motor functions, facilitating the development of dynamic and personalized rehabilitation plans. It enables remote rehabilitation assessments, allowing patients to perform exercises under virtual supervision. It shows potential for enhancing the objectivity and accuracy of assessments compared to traditional methods, streamline clinical workflows, and support proactive management of rehabilitation plans. CONCLUSIONS As an innovative advancement in post-stroke rehabilitation, the IMFAS addresses critical limitations of traditional assessment methods by providing comprehensive, accurate, and quantifiable assessments. By leveraging multi-data fusion and AI technologies, the system enhances the personalization and effectiveness of post-stroke rehabilitation strategies and demonstrates potential for broader adoption in clinical settings. Further research and development are necessary to optimize the current functions, evaluate its clinical performance, and expand its its integration into routine clinical practice.

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Real-Time Monitoring for Knee Extensor Muscle Training With Flexible Sensors

Cited by 2 publications

References 9 publications

Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review

Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review

Developing an Intelligent Motor Function Assessment System (IMFAS) for post-stroke rehabilitation using multi-data fusion (Preprint)

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