A Nonproprietary Movement Analysis System (MoJoXlab) Based on Wearable Inertial Measurement Units Applicable to Healthy Participants and Those With Anterior Cruciate Ligament Reconstruction Across a Range of Complex Tasks: Validation Study.
Riasat IslamMohamed BennasarKevin NicholasKate ButtonSimon HollandPaul MulhollandBlaine A PriceMohammad Al-AmriPublished in: JMIR mHealth and uHealth (2020)
This study demonstrates that nonproprietary software such as MoJoXlab can accurately calculate joint angles for movement analysis applications comparable with proprietary software for walking, squatting, and jumping in healthy individuals and those following ACL reconstruction. MoJoXlab can be used with generic wearable IMUs that can provide clinicians accurate objective data when assessing patients' movement, even when changes are too small to be observed visually. The availability of easy-to-setup, nonproprietary software for calibration, data collection, and joint angle calculation has the potential to increase the adoption of wearable IMU sensors in clinical practice, as well as in free living conditions, and may provide wider access to accurate, objective assessment of patients' progress over time.
Keyphrases
- end stage renal disease
- newly diagnosed
- ejection fraction
- electronic health record
- clinical practice
- prognostic factors
- peritoneal dialysis
- heart rate
- data analysis
- anterior cruciate ligament reconstruction
- patient reported outcomes
- machine learning
- blood pressure
- big data
- risk assessment
- deep learning
- working memory