Accurate Prediction of Knee Angles during Open-Chain Rehabilitation Exercises Using a Wearable Array of Nanocomposite Stretch Sensors

Wood, David; Jensen, Kurt Villads; Crane, Allison; Lee, Hyunwook; Dennis, Hayden E.; Gladwell, Joshua; Shurtz, Anne; Fullwood, David T.; Seeley, Matthew K.; Mitchell, Ulrike H.; Christensen, William F.; Bowden, Anton E.

doi:10.3390/s22072499

Cited by 14 publications

(3 citation statements)

References 77 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…12 , the RMSEs ranged from 4.7° to 7.0° in the cycling experiments for the human joint. The RMSE and R 2 in the cycling experiment were slightly lower in accuracy than those in the bending test because the attachment positions of the bending angle sensor based on double-layer capacitance on the patella differed from the anchored marker positions [17] , [26] , [28] . The output voltages of the bending angle sensor based on double-layer capacitance delayed the cycles.…”

Section: Discussionmentioning

confidence: 85%

Bending Angle Sensor Based on Double-Layer Capacitance Suitable for Human Joint

Goto

Sakaue

Kobayashi

et al. 2023

IEEE Open J. Eng. Med. Biol.

View full text Add to dashboard Cite

Goal : To develop bending angle sensors based on double-layer capacitance for monitoring joint angles during cycling exercises. Methods : We develop a bending angle sensor based on double-layer capacitive and conducted three stretching, bending, and cycling tests to evaluate its validity. Results : We demonstrate that the bending angle sensor based on double-layer capacitance minimizes the change in the capacitance difference in the stretching test. The hysteresis and root mean square error (RMSE) compared with the optical motion capture show hysteresis: 8.0% RMSE and 3.1° in the bending test. Moreover, a cycling experiment for human joint angle measurements confirm the changes in accuracy. The RMSEs ranged from 4.7° to 7.0°, even when a human wears leggings fixed with the developed bending-angle sensor in the cycling test. Conclusion : The developed bending angle sensor provides a practical application of the quantitative and observational evaluation tool for knee joint angles.

show abstract

Section: Discussionmentioning

confidence: 85%

Bending Angle Sensor Based on Double-Layer Capacitance Suitable for Human Joint

Goto

Sakaue

Kobayashi

et al. 2023

IEEE Open J. Eng. Med. Biol.

View full text Add to dashboard Cite

show abstract

“…Wood et al developed 3 knee sleeve devices equipped with 16 piezoresistive sensors to calculate knee joint angles for at-home knee rehabilitation. 51 To assess the accuracy of their device, they recruited 18 healthy participants to perform open-chain knee flexion exercises. They used 18 ML regressors to predict joint angles.…”

Section: Resultsmentioning

confidence: 99%

Technological advances in lower-limb tele-rehabilitation: A review of literature

Ettefagh,

Roshan Fekr

2024

Journal of Rehabilitation and Assistive Technologies Engineerin

View full text Add to dashboard Cite

Tele-rehabilitation is a healthcare practice that leverages technology to provide rehabilitation services remotely to individuals in their own homes or other locations. With advancements in remote monitoring and Artificial Intelligence, automatic tele-rehabilitation systems that can measure joint angles, recognize exercises, and provide feedback based on movement analysis are being developed. Such platforms can offer valuable information to clinicians for improved care planning. However, with various methods and sensors being used, understanding their pros, cons, and performance is important. This paper reviews and compares the performance of recent vision-based, wearable, and pressure-sensing technologies used in lower limb tele-rehabilitation systems over the past 10 years (from 2014 to 2023). We selected studies that were published in English and focused on joint angle estimation, activity recognition, and exercise assessment. Vision-based approaches were the most common, accounting for 42% of studies. Wearable technology followed at approximately 37%, and pressure-sensing technology appeared in 21% of studies. Identified gaps include a lack of uniformity in reported performance metrics and evaluation methods, a need for cross-subject validation, inadequate testing with patients and older adults, restricted sets of exercises evaluated, and a scarcity of comprehensive datasets on lower limb exercises, especially those involving movements while lying down.

show abstract

“…This makes it possible to detect small physiological changes from baseline values over time and provides a new tool for medical personnel to continuously obtain health-quality data from their patients [1]. The strain wearable sensors can capture the motion state and posture of different parts of the human body which is crucial for rehabilitation therapy applications [2][3][4][5][6][7]. In this regard, piezoresistive sensors have been widely explored due to their low fabrication costs and ease of signal acquisition [8,9].…”

Section: Introductionmentioning

confidence: 99%

Novel Smart Wearable Sensors Based on PVDF Reinforced With CNTs for Human Motion Monitoring

Díaz Mena,

Romate,

Díaz

et al. 2024

IEEE Sensors J.

View full text Add to dashboard Cite

Wearable strain sensors based on Poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) reinforced with carbon nanotubes (CNTs) dispersed with Triton surfactant by solvent casting are proposed. The analysis of the electrical response shows that the conductivity increases with CNT content, as expected, whereas the addition of a high content of surfactant is more efficient at low CNT contents as it forms a more efficient electrical network. An AC analysis with Electrochemical Impedance Spectroscopy was carried out, where the variation in Rint/Rtunnel ratio with CNT and surfactant content was analyzed. This ratio shows when the electrical pathway is saturated and the electrical transport occurs mainly through the aggregates, or when the tunneling mechanism starts to take relevance. Electromechanical analysis under tensile loading shows that the sensitivity increases with decreasing the CNT content, reaching gauge factor (GF) values of around 10 4 at 80-90 % strain level, higher than most of the research found in the literature. Furthermore, the electrical response under cycling loading shows similar peak and base values between consecutive cycles in a medium-term response, highlighting the robustness of the sensors. Finally, the sensors are subjected to a proof-of-concept test for finger and elbow movement monitoring, where a good agreement between the electrical and mechanical response is observed, demonstrating the applicability of the proposed materials for monitoring medium and large human movements.

show abstract

Accurate Prediction of Knee Angles during Open-Chain Rehabilitation Exercises Using a Wearable Array of Nanocomposite Stretch Sensors

Cited by 14 publications

References 77 publications

Bending Angle Sensor Based on Double-Layer Capacitance Suitable for Human Joint

Bending Angle Sensor Based on Double-Layer Capacitance Suitable for Human Joint

Technological advances in lower-limb tele-rehabilitation: A review of literature

Novel Smart Wearable Sensors Based on PVDF Reinforced With CNTs for Human Motion Monitoring

Contact Info

Product

Resources

About