Depth Mapping for Neurodegenerative Disease Assessment
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Solution Overview
Problem
Current diagnostic methods for movement disorders like Parkinson's Disease and Essential Tremor are subjective, require bulky sensors, and are limited to clinical settings, making long-term monitoring and treatment evaluation challenging due to discomfort and fatigue issues in patients.
Innovation Solution
A depth mapping system captures three-dimensional user movements during everyday activities, comparing them to baseline models or machine learning models to detect motion features indicative of chronic neurodegenerative conditions, enabling remote and continuous monitoring and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If bulky sensors are used to track lower extremity freezing, then measurement precision is improved, but device complexity and user comfort deteriorate
Solution Approach 1:
The patent replaces mechanical sensors worn on the body with optical depth mapping systems that capture motion data remotely. The depth mapping system uses optical fields to detect and track body movements, eliminating the need for physical sensors attached to the patient's lower extremities.
Solution Approach 2:
The patent creates a digital copy of the patient's motion patterns through depth mapping. Instead of physically sensing movements, the system captures optical images and reconstructs motion data computationally, providing an accurate representation of gait and freezing episodes without physical contact.
2Measurement precision
If clinical assessments are conducted in practitioner's office, then measurement precision is improved, but adaptability deteriorates due to patient discomfort and fatigue
Solution Approach 1:
The patent enables patients to conduct self-assessments in their own environments using the depth mapping system. The system allows individuals to monitor their own movements and generate diagnostic data without requiring practitioner presence or clinical facility access, making the assessment process self-sufficient and adaptable to various settings.
Solution Approach 2:
The depth mapping system is designed to function universally across multiple environments including homes, clinics, and outdoor settings. The same system can capture motion data for various diagnostic purposes and different patient populations, providing versatile monitoring capabilities beyond traditional clinical boundaries.
3Device complexity
If brief period assessments are used in clinic, then device complexity is reduced, but loss of information increases due to inability to capture long-term symptom severity
Solution Approach 1:
The patent implements continuous motion capture over extended periods, allowing the depth mapping system to record movements throughout the day and across multiple days. This continuous monitoring captures the full range and severity of symptoms including intermittent freezing episodes that brief assessments would miss, providing comprehensive longitudinal data.
Solution Approach 2:
The system performs preliminary data collection and processing locally, storing motion data for later analysis. The depth mapping system continuously captures and pre-processes motion information, preparing comprehensive datasets in advance that can be analyzed to identify patterns and severity metrics that would be impossible to detect in brief clinic visits.
Data Source
AI summary
An apparatus, system and process for tracking and analyzing target person movements, captured while the target person is performing ordinary tasks outside of a medical context, for medical diagnosis and treatment review are described. The method may include constructing a model of a target person from three-dimensional (3D) image data of the target person performing an activity over a period of time. The method may also include tracking movement of the model of the target person in the 3D image data over the period of time, and detecting one or more motion features in the movement of the model of the target person that are relevant to diagnosis, treatment, care, or a combination thereof, of a potential chronic neurodegenerative or musculoskeletal medical condition. The method may also include computing a risk score associated with likelihood of the target person having the medical condition based on the detected motion features.