AIoT-Powered Wearable System for Real-Time Monitoring and Detection of Drug-Induced Orthostatic Hypotension, Body Posture, and Patient Discomfort

基 于 AIoT 的可穿戴系统 用于药物诱导性直立性低血压、体态及患者不适的实时监测与检测

50,000

Orthostatic Hypotension (OH) is a common, non-motor symptom that is highly detrimental in the cases of Parkinson’s disease and Parkinsonism. The most common cause of OH is the dual effect of neurodegenerative autonomic dysfunction and anti-Parkinson medications. Current recognition, monitoring, and measurement of OH is insufficient with low detection rates, leading to significant complications during treatment. Currently, traditional methods are inconsistent and provide inaccurate measurements and detection, specifically when establishing risk profiles of drug-induced OH. A systematic, intelligent, real-time wearable solution is essential to enable patients to identify differential risks related to medications, their prevention and self-management. Therefore, a systematic identification and interpretation of the epidemiological characteristics, risk factors, and clinical management of OH – particularly drug‑induced OH – in PD and parkinsonism has substantial theoretical and clinical value for early identification of high‑risk patients, optimisation of pharmacological regimens, and improvement of patients’ quality of life and long‑term prognosis. This project proposes the development of AI-based wearable IoT solution to address the stated critical problem and provide real-time insights to patients and clinicians alike.