2 research outputs found
Validation of a Lower Back “Wearable”-Based Sit-to-Stand and Stand-to-Sit Algorithm for Patients With Parkinson's Disease and Older Adults in a Home-Like Environment
Introduction: Impaired sit-to-stand and stand-to-sit movements (postural transitions,
PTs) in patients with Parkinson’s disease (PD) and older adults (OA) are associated with
risk of falling and reduced quality of life. Inertial measurement units (IMUs, also called
“wearables”) are powerful tools to monitor PT kinematics. The purpose of this study was
to develop and validate an algorithm, based on a single IMU positioned at the lower
back, for PT detection and description in the above-mentioned groups in a home-like
environment.
Methods: Four PD patients (two with dyskinesia) and one OA served as algorithm
training group, and 21 PD patients (16 without and 5 with dyskinesia) and 11 OA
served as test group. All wore an IMU on the lower back and were videotaped
while performing everyday activities for 90–180min in a non-standardized home-like
environment. Accelerometer and gyroscope signals were analyzed using discrete wavelet
transformation (DWT), a six degrees-of-freedom (DOF) fusion algorithm and vertical
displacement estimation.
Results: From the test group, 1,001 PTs, defined by video reference, were
analyzed. The accuracy of the algorithm for the detection of PTs against video
observation was 82% for PD patients without dyskinesia, 47% for PD patients with
dyskinesia and 85% for OA. The overall accuracy of the PT direction detection
was comparable across groups and yielded 98%. Mean PT duration values were
1.96 s for PD patients and 1.74 s for OA based on the algorithm (p < 0.001) and
1.77 s for PD patients and 1.51 s for OA based on clinical observation (p < 0.001).
Conclusion: Validation of the PT detection algorithm in a home-like environment shows
acceptable accuracy against the video reference in PD patients without dyskinesia and
controls. Current limitations are the PT detection in PD patients with dyskinesia and the
use of video observation as the video reference. Potential reasons are discussed
Validation of a Lower Back “Wearable”-Based Sit-to-Stand and Stand-to-Sit Algorithm for Patients With Parkinson's Disease and Older Adults in a Home-Like Environment
Introduction: Impaired sit-to-stand and stand-to-sit movements (postural transitions, PTs) in patients with Parkinson's disease (PD) and older adults (OA) are associated with risk of falling and reduced quality of life. Inertial measurement units (IMUs, also called “wearables”) are powerful tools to monitor PT kinematics. The purpose of this study was to develop and validate an algorithm, based on a single IMU positioned at the lower back, for PT detection and description in the above-mentioned groups in a home-like environment.Methods: Four PD patients (two with dyskinesia) and one OA served as algorithm training group, and 21 PD patients (16 without and 5 with dyskinesia) and 11 OA served as test group. All wore an IMU on the lower back and were videotaped while performing everyday activities for 90–180 min in a non-standardized home-like environment. Accelerometer and gyroscope signals were analyzed using discrete wavelet transformation (DWT), a six degrees-of-freedom (DOF) fusion algorithm and vertical displacement estimation.Results: From the test group, 1,001 PTs, defined by video reference, were analyzed. The accuracy of the algorithm for the detection of PTs against video observation was 82% for PD patients without dyskinesia, 47% for PD patients with dyskinesia and 85% for OA. The overall accuracy of the PT direction detection was comparable across groups and yielded 98%. Mean PT duration values were 1.96 s for PD patients and 1.74 s for OA based on the algorithm (p < 0.001) and 1.77 s for PD patients and 1.51 s for OA based on clinical observation (p < 0.001).Conclusion: Validation of the PT detection algorithm in a home-like environment shows acceptable accuracy against the video reference in PD patients without dyskinesia and controls. Current limitations are the PT detection in PD patients with dyskinesia and the use of video observation as the video reference. Potential reasons are discussed