Patients with advanced Parkinson's disease regularly experience unstable motor states. Objective and reliable monitoring of these fluctuations is an unmet need. We used deep learning to classify motion data from a single wrist-worn IMU sensor recordi...
To evaluate movement quality of upper limb (UL) prosthesis users, performance-based outcome measures have been developed that examine the normalcy of movement as compared to a person with a sound, intact hand. However, the broad definition of "normal...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
36086065
The collection of Parkinson's Disease (PD) time-series data usually results in imbalanced and incomplete datasets due to the geometric distribution of PD complications' sever-ity scores. Consequently, when training deep convolutional models on these ...
BACKGROUND: Robot-assisted training is used as a new rehabilitation training method for the treatment of motor dysfunction in neurological diseases. Robot-assisted gait training (RAGT) has been reported to treat motor dysfunction in patients with Par...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
39383074
Motor symptoms such as tremor and bradykinesia can develop concurrently in Parkinson's disease; thus, the ideal home monitoring system should be capable of tracking symptoms continuously despite background noise from daily activities. The goal of thi...
A common shoulder problem that significantly detracts from patients' quality of life is shoulder instability (SI). Abnormal scapular positioning and movement are closely associated with rotator cuff injuries and SI, as shown by several studies. The a...