Mobile Application for Continuous Monitoring and Severity Assessment of Neurological Disorders Using Accelerometer Data and Machine Learning

Current clinical assessments of neurological diseases, such as Parkinson's, are limited to infrequent in-person evaluations, providing only a snapshot of the patient's condition. This leads to challenges in accurately tracking disease progression and adjusting treatments effectively, especially given the symptom fluctuations over short periods. There is a need for a continuous, objective, and accessible assessment method leveraging mobile technology to enhance disease management and early detection.

A mid-sized healthcare organization or research institution seeking innovative tools for monitoring neurological disease progression and early detection through patient-centered mobile solutions.

• Develop a mobile application enabling continuous collection of sensor data related to neurological symptoms, primarily via accelerometer data.
• Implement machine learning algorithms to analyze sensor data and objectively assess symptom severity and progression over time.
• Provide healthcare professionals with detailed, reliable insights into patients' fluctuating conditions to improve treatment adjustments and early detection of disease onset.
• Enhance patient engagement with easy-to-use monitoring tools and promote proactive disease management.

• Integration with smartphone accelerometers to collect high-frequency sensor data relevant to neurological symptoms.
• Data processing module for real-time analysis of accelerometer signals to detect changes in symptom metrics.
• Machine learning algorithms trained to evaluate symptom severity, including finger tapping speed, reaction time, balance, and gait patterns.
• RESTful API for data exchange, storage, and integration with healthcare data systems.
• User interface allowing patients to perform assessments and view their symptom reports.

• Healthcare data management systems for integrating assessment data
• Potential integration with electronic health records (EHR) for comprehensive patient profiles

• Scalable architecture capable of handling increasing user base and data volume
• High data security and patient privacy compliance (e.g., GDPR, HIPAA)
• Real-time data processing with minimal latency
• High availability and reliability

The deployment of the mobile monitoring app is expected to enable objective, continuous assessment of neurological symptoms, leading to more accurate tracking of disease progression and earlier detection. This can reduce the frequency of in-clinic visits, improve treatment personalization, and ultimately enhance patient outcomes. Quantitatively, it aims to provide objective assessments that are less reliant on subjective observations, resulting in improved diagnosis accuracy and treatment adjustments.