Mobile Sensor Assessment for Early Neurological Diagnosis
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Solution Overview
Problem
Traditional methods for diagnosing neurological diseases like Parkinson's disease are costly, complex, and not accessible to many individuals, leading to delayed diagnosis and misdiagnosis.
Innovation Solution
A system using mobile electronic devices with sensors and machine learning algorithms to collect and analyze motor and non-motor function data over time, providing a clinical assessment of neurological conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional radiological brain imaging tests (e.g., DaTscan) are used for diagnosis, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a simplified copy of the diagnostic process by using mobile device sensors to replicate the functionality of complex radiological imaging. Instead of requiring actual DaTscan imaging, the system uses accelerometer data from smartphone sensors as a proxy measurement that correlates with dopamine transporter binding, providing diagnostic information through a simplified modal
2Measurement precision
If traditional radiological brain imaging tests (e.g., DaTscan) are used for diagnosis, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent replaces expensive, resource-intensive radiological imaging with a low-cost alternative using disposable or reusable mobile device sensors. The accelerometer-based measurement requires no specialized imaging equipment, radioactive tracers, or complex processing facilities, making the diagnostic tool economically accessible while maintaining diagnostic precision
3Measurement precision
If traditional radiological brain imaging tests are used for diagnosis, then measurement precision is improved, but accessibility decreases
Solution Approach 1:
The patent leverages the universality of mobile devices that most people already possess. By using the accelerometer sensor built into smartphones and tablets, the system transforms a common consumer device into a diagnostic tool, eliminating the need for specialized medical equipment and making the diagnostic capability universally accessible through devices people already carry
4Reliability
If traditional clinical assessment methods are used, then reliability is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary data collection continuously in the background using the mobile device accelerometer before the actual diagnostic assessment is needed. The system pre-collects baseline motor function data and environmental information, so that when diagnostic evaluation is required, the data is already available for immediate analysis, eliminating lengthy testing sessions
Data Source
AI summary
The present disclosure provides systems and methods for performing a clinical assessment of a neurological disease, disorder, or condition. In an aspect, a system may comprise sensors, which sensors are configured to acquire sensor data of the subject over a period of time; and which mobile electronic device, comprises: an electronic display; a wireless transceiver; and one or more computer processors configured to (i) receive the sensor data from the sensors, (ii) process the sensor data or features extracted therefrom using a trained algorithm to generate an output indicative of a state of a neurological disease, disorder, or condition of the subject, and (iii) based at least in part on the generated output, perform a clinical assessment on the subject.