TY - GEN
T1 - Aerobic Exercise System for Home Telerehabilitation
AU - Smiley, Aref
AU - Finkelstein, Joseph
N1 - Funding Information:
The project is funded in part by NIH grant R33HL143317.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The COVID-19 pandemic has impacted every aspect of health delivery and encouraged to replace in-person clinical visits with telecommunications. By providing wireless communication between embedded electronic devices and sensors, telerehabilitation enables constant monitoring of vital body functions, and tracking of physical activities of a person and aids physical therapy. In this paper, we designed and tested two remotely controlled versions of interactive bike (iBikE) systems which communicate through either Wi-Fi or BLE and give the clinical team the capability to monitor exercise progress in real time using simple graphical representation. We used the same hardware and user interface for both designs. The software uses either Wi-Fi or BLE protocol to connect the iBikE equipment and PC tablet. The bike can be used for upper or lower limb rehabilitation. A customized tablet app was developed to provide user interface between the app and the bike sensors. Both bikes were tested with a single group of nine individuals in two separate sessions. Each individual was asked to hand-cycle for three separate sub-sessions (1 minute each for slow, medium, and fast pace) with one-minute rest. During each sub-session, speed of the bikes was measured continuously using a tachometer, in addition to reading speed values from the iBikE app, to compare the functionality and accuracy of the measured data. Measured RPMs in each sub-session from iBikE and tachometer were further divided into 4 categories: 10-second bins (6 bins), 20-second bins (3 bins), 30-second bins (2 bins), and RPMs in each sub-session (1 minute, 1 bin). Then, the mean difference of each category (iBikE, tachometer) was calculated for each sub-session. Finally, mean and standard deviation (SD) of the calculated mean differences were reported for all individuals. We saw decreasing trend in both mean and SD from 10 second to 1 minute measurement. For BLE iBikE system, minimum mean RPM difference was 0.2 \pm 0.3 in one-minute sub-session with medium speed. This number was 0.21 \pm 0.21 in one-minute sub-session with slow speed for Wi-Fi iBikE system. Thus, testing confirmed high accuracy of our interfaces.
AB - The COVID-19 pandemic has impacted every aspect of health delivery and encouraged to replace in-person clinical visits with telecommunications. By providing wireless communication between embedded electronic devices and sensors, telerehabilitation enables constant monitoring of vital body functions, and tracking of physical activities of a person and aids physical therapy. In this paper, we designed and tested two remotely controlled versions of interactive bike (iBikE) systems which communicate through either Wi-Fi or BLE and give the clinical team the capability to monitor exercise progress in real time using simple graphical representation. We used the same hardware and user interface for both designs. The software uses either Wi-Fi or BLE protocol to connect the iBikE equipment and PC tablet. The bike can be used for upper or lower limb rehabilitation. A customized tablet app was developed to provide user interface between the app and the bike sensors. Both bikes were tested with a single group of nine individuals in two separate sessions. Each individual was asked to hand-cycle for three separate sub-sessions (1 minute each for slow, medium, and fast pace) with one-minute rest. During each sub-session, speed of the bikes was measured continuously using a tachometer, in addition to reading speed values from the iBikE app, to compare the functionality and accuracy of the measured data. Measured RPMs in each sub-session from iBikE and tachometer were further divided into 4 categories: 10-second bins (6 bins), 20-second bins (3 bins), 30-second bins (2 bins), and RPMs in each sub-session (1 minute, 1 bin). Then, the mean difference of each category (iBikE, tachometer) was calculated for each sub-session. Finally, mean and standard deviation (SD) of the calculated mean differences were reported for all individuals. We saw decreasing trend in both mean and SD from 10 second to 1 minute measurement. For BLE iBikE system, minimum mean RPM difference was 0.2 \pm 0.3 in one-minute sub-session with medium speed. This number was 0.21 \pm 0.21 in one-minute sub-session with slow speed for Wi-Fi iBikE system. Thus, testing confirmed high accuracy of our interfaces.
KW - home-based exercise
KW - remote cycling
KW - telerehabilitation
KW - wireless interface
UR - http://www.scopus.com/inward/record.url?scp=85137914606&partnerID=8YFLogxK
U2 - 10.1109/CBMS55023.2022.00059
DO - 10.1109/CBMS55023.2022.00059
M3 - Conference contribution
AN - SCOPUS:85137914606
T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems
SP - 297
EP - 301
BT - Proceedings - 2022 IEEE 35th International Symposium on Computer-Based Medical Systems, CBMS 2022
A2 - Shen, Linlin
A2 - Gonzalez, Alejandro Rodriguez
A2 - Santosh, KC
A2 - Lai, Zhihui
A2 - Sicilia, Rosa
A2 - Almeida, Joao Rafael
A2 - Kane, Bridget
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2022
Y2 - 21 July 2022 through 23 July 2022
ER -