Closing the Wearable Gap—Part III: Use of Stretch Sensors in Detecting Ankle Joint Kinematics During Unexpected and Expected Slip and Trip Perturbations
| Autor: | Raj Prabhu, Reuben F. Burch, Tony Luczak, Phuoc Nguyen, Harish Chander, Brian K. Smith, Adam C. Knight, John E. Ball, Ethan M. Stewart, David Saucier |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
medicine.medical_specialty
trips Computer Networks and Communications Physics::Medical Physics lcsh:TK7800-8360 Slip (materials science) Kinematics 01 natural sciences Motion capture Computer Science::Robotics Physical medicine and rehabilitation falls medicine 0501 psychology and cognitive sciences Electrical and Electronic Engineering Treadmill Joint (geology) 050107 human factors Balance (ability) Quantitative Biology::Neurons and Cognition 010401 analytical chemistry 05 social sciences lcsh:Electronics stretch-sensors 0104 chemical sciences ankle kinematics medicine.anatomical_structure wearables Hardware and Architecture Control and Systems Engineering Signal Processing Ankle Range of motion human activities Geology postural perturbations slips |
| Zdroj: | Electronics Volume 8 Issue 10 Electronics, Vol 8, Iss 10, p 1083 (2019) |
| ISSN: | 2079-9292 |
| DOI: | 10.3390/electronics8101083 |
| Popis: | Background: An induced loss of balance resulting from a postural perturbation has been reported as the primary source for postural instability leading to falls. Hence early detection of postural instability with novel wearable sensor-based measures may aid in reducing falls and fall-related injuries. The purpose of the study was to validate the use of a stretchable soft robotic sensor (SRS) to detect ankle joint kinematics during both unexpected and expected slip and trip perturbations. Methods: Ten participants (age: 23.7 ± 3.13 years height: 170.47 ± 8.21 cm mass: 82.86 ± 23.4 kg) experienced a counterbalanced exposure of an unexpected slip, an unexpected trip, an expected slip, and an expected trip using treadmill perturbations. Ankle joint kinematics for dorsiflexion and plantarflexion were quantified using three-dimensional (3D) motion capture through changes in ankle joint range of motion and using the SRS through changes in capacitance when stretched due to ankle movements during the perturbations. Results: A greater R-squared and lower root mean square error in the linear regression model was observed in comparing ankle joint kinematics data from motion capture with stretch sensors. Conclusions: Results from the study demonstrated that 71.25% of the trials exhibited a minimal error of less than 4.0 degrees difference from the motion capture system and a greater than 0.60 R-squared value in the linear model suggesting a moderate to high accuracy and minimal errors in comparing SRS to a motion capture system. Findings indicate that the stretch sensors could be a feasible option in detecting ankle joint kinematics during slips and trips. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|