Wearable Movement Detection for Psychological Disorder Diagnosis
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Solution Overview
Problem
Current methods for diagnosing psychiatric disorders, such as ADHD, are subjective and lack a convenient way to identify disorders through movement patterns, as they rely on clinical observations rather than objective data analysis.
Innovation Solution
A method involving a device worn by the individual to record movement and optional heart rate data, which is analyzed using an Artificial Neural Network to determine the presence of specific psychological disorders by calculating distinctive parameter sets and comparing data before and after drug administration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If clinical observations are used for diagnosis, then diagnostic capability is maintained, but objectivity and reliability are poor
Solution Approach 1:
The patent replaces subjective clinical observation with an automated electronic system that uses accelerometers to objectively measure and analyze movement patterns. This substitution of mechanical measurement for human judgment directly improves diagnostic objectivity while the automated analysis reduces the complexity burden through algorithmic processing.
Solution Approach 2:
The patent introduces an intermediary computational system that processes raw movement data through feature extraction and pattern recognition algorithms. This intermediary layer transforms complex raw data into meaningful diagnostic indicators, managing system complexity by breaking down the analysis into manageable computational stages.
2Reliability
If movement pattern analysis is implemented, then diagnostic reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The patent implements self-service through automated data collection where the accelerometer continuously and passively records movement patterns without requiring active participant engagement. The system automatically processes data through feature extraction and comparison algorithms, eliminating manual intervention and maintaining ease of operation while ensuring reliable diagnostic analysis.
3Measurement precision
If detailed movement data is collected, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent applies preliminary action by continuously collecting and storing movement data in real-time during normal activity periods. This pre-collection approach allows the system to have data ready for immediate analysis when needed, improving measurement precision through comprehensive data capture while reducing time loss by avoiding delayed data gathering.
Solution Approach 2:
The patent extracts only the essential diagnostic features from comprehensive movement data through feature extraction algorithms. By taking out and analyzing only the most relevant movement characteristics rather than processing all raw data, the system achieves high measurement precision while minimizing processing time through selective analysis.
Data Source
AI summary
A method for detecting a psychological disorder in a person comprises collecting movement and, optionally, other data from the person by a device borne by the person; storing the data in a memory in contact with the device during the collection of data; transferring the stored data to a computer; calculating at least one set of parameter data distinctive of the movement data; feeding the least one set of parameter data to an Artificial Neural Network trained to recognize in the data a feature specific for a psychological disorder or a group of such disorders. Also is disclosed an assembly for carrying out the method.