To systematically review progress and challenges in remote monitoring platforms for Parkinson's Disease (PD) from 2019 to the present, focusing on clinical performance, algorithmic approaches, and clinical translation.
Key Findings:
Wearable sensors show promise in quantifying both motor and nonmotor symptoms of PD, with specific examples of sensor types.
Algorithmic approaches vary in efficiency and face persistent challenges in feature extraction, particularly in real-time applications.
Current integration of remote monitoring platforms into clinical practice is limited by translational obstacles, including regulatory and technological barriers.
Interpretation:
The review highlights the potential of intelligent multimodal monitoring to improve PD management but underscores the need for better integration and real-time monitoring capabilities.
Limitations:
The review is not a fully exhaustive systematic review, which may limit comprehensiveness and the generalizability of findings.
Focus on literature published only between 2019 and 2024 may exclude relevant earlier studies, potentially overlooking foundational research.
Conclusion:
Advancements in intelligent monitoring technologies for PD present significant opportunities for enhancing patient care, but successful clinical adoption requires overcoming existing barriers, particularly in integration and real-time monitoring capabilities.
