Motion Detection Device for Cerebral Infarction Screening
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Solution Overview
Problem
Current methods for detecting cerebral infarction often fail to identify transient symptoms or those unnoticed by individuals, leading to delayed detection and worsening of the condition.
Innovation Solution
An information processing device that utilizes motion detection sensors to analyze daily motion patterns and compare them to baseline data, determining the presence of abnormal states indicative of cerebral infarction by detecting differences in motion between the left and right halves of the body.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If active participation in diagnosis is required, then detection accuracy can be improved, but detection coverage deteriorates because transient or unnoticed symptoms are missed
Solution Approach 1:
The system performs self-diagnosis by automatically monitoring motion patterns without requiring active participation from the subject. Motion detection sensors continuously capture body movements, and the determination unit automatically compares these patterns against baseline data to identify abnormalities, enabling the system to diagnose itself without human intervention.
Solution Approach 2:
Motion detection sensors serve as intermediaries that objectively capture and transmit motion pattern data to the determination unit. This intermediary mechanism allows the system to detect symptoms that the subject may not consciously perceive or report, bridging the gap between subjective awareness and objective detection.
2Reliability
If passive monitoring is implemented, then detection coverage is improved, but detection accuracy deteriorates due to inability to capture transient symptoms
Solution Approach 1:
The motion detection sensors continuously monitor body movements without interruption, ensuring that transient symptoms are captured as they occur. This continuous monitoring maintains constant detection coverage, preventing any gaps where symptoms might go unnoticed.
Solution Approach 2:
The system compares real-time motion patterns against baseline data and provides immediate determination of abnormalities. This feedback mechanism enables the system to quickly identify and report transient symptoms, improving detection accuracy through continuous comparison and analysis.
3Loss of information
If manual symptom reporting is used, then subject awareness is improved, but detection timeliness deteriorates due to delay in reporting
Solution Approach 1:
The system replaces the mechanical process of manual symptom reporting with automated motion detection and analysis. Motion sensors objectively capture body movements and the determination unit automatically identifies abnormalities, eliminating the time delay associated with human reporting while maintaining accurate symptom detection.
4Measurement precision
If invasive diagnostic procedures are performed, then detection accuracy is improved, but subject comfort deteriorates
Solution Approach 1:
The system replaces invasive diagnostic procedures with non-invasive motion detection technology. Motion sensors capture body movements externally without requiring physical intrusion into the body, maintaining detection accuracy through objective motion pattern analysis while completely avoiding the discomfort associated with invasive methods.
Data Source
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AI summary
An information processing method causes a computer to execute processing of: acquiring motion information detected by a motion detection device that detects a motion of a subject; storing the acquired motion information in a storage unit; deriving reference motion information on a left half body and reference motion information on a right half body of the subject, based on the stored motion information in a predetermined period; and determining whether an abnormal state in which there is a possibility of cerebral infarction in the subject is present based on the derived reference motion information, and motion information on a left half body and motion information on a right half body of the subject at a detection time subsequent to the predetermined period.