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In-Bed Mobility Monitoring Using Pressure Sensors.

, , , , and . IEEE Trans. Instrumentation and Measurement, 64 (8): 2110-2120 (2015)

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Applications of Data mining in a Web-enabled Caregiver-Report Tool for Symptom Relations in Dementia., , and . DMIN, page 214-220. CSREA Press, (2007)Interpretable machine learning for high-dimensional trajectories of aging health., , , and . CoRR, (2021)Requirements gathering with Alzheimer's patients and caregivers., , , , and . ASSETS, page 142-149. ACM, (2005)Comparison of Machine Learning Techniques with Classical Statistical Models in Predicting Health Outcomes., , , and . MedInfo, volume 107 of Studies in Health Technology and Informatics, page 736-740. IOS Press, (2004)In-Bed Mobility Monitoring Using Pressure Sensors., , , , and . IEEE Trans. Instrumentation and Measurement, 64 (8): 2110-2120 (2015)Monitoring the relief of pressure points for pressure ulcer prevention: A subject dependent approach., , , and . MeMeA, page 135-138. IEEE, (2013)Automated assessment of mobility in bedridden patients., , , and . EMBC, page 4271-4274. IEEE, (2013)Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources., , , and . Data Sci. J., (2003)Interpretable machine learning for high-dimensional trajectories of aging health., , , and . PLoS Comput. Biol., (2022)Distinguishing between stable and unstable sit-to-stand transfers using pressure sensors., , , and . MeMeA, page 76-79. IEEE, (2014)