Wearable Technology and Machine Learning for Prediction of Performance-Based and Patient-Reported Outcome Measures: A Systematic Review

Abstract

Machine learning models informed by patient-generated wearable data can be used to predict patient-reported and performance-based outcome measures. This approach offers a promising alternative to traditional outcome monitoring, which is commonly limited by recall bias, discrete sampling, and healthcare resource constraints. The aims of this systematic review were to identify wearable-derived features strongly associated with performance-based and patient-reported outcome measures, to compare the predictive performance across machine learning approaches, and to consolidate methodological limitations and provide suggestions for future work. Following a systematic search of four databases (PubM..