Capacitive Hand Training Device for Individual Finger Strength Measurement
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Solution Overview
Problem
Current hand rehabilitation devices lack the ability to provide biofeedback, are not cost-effective, and consume excessive power, failing to accurately measure individual finger strength and movement, leading to inefficiencies in patient monitoring and rehabilitation.
Innovation Solution
A hand training device equipped with capacitive sensors and a processor that generates a 3-dimensional model of the hand to measure grip and pinch strength, providing real-time biofeedback and remote monitoring, while reducing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If magnetic sensing or strain gauges are used to detect force, then force measurement capability is provided, but cost-effectiveness deteriorates
Solution Approach 1:
The patent replaces magnetic sensing and strain gauge systems with capacitive sensing technology. The capacitive sensors detect hand position and deformation through electrical field interactions rather than mechanical or magnetic means, significantly reducing component costs while maintaining measurement capability. This substitution directly addresses the contradiction by eliminating expensive magnetic and mechanical sensing components.
2Measurement precision
If 3-dimensional shape calculation and movement tracking are performed, then measurement accuracy is improved, but power consumption increases
Solution Approach 1:
The patent implements optimized 3-dimensional modeling that calculates only the necessary hand position and deformation parameters required for rehabilitation measurement, rather than performing exhaustive calculations on all possible hand movements. This selective approach maintains measurement accuracy for clinically relevant parameters while significantly reducing computational power consumption.
3Ease of operation
If conventional rehabilitation devices are used, then basic exercise support is provided, but biofeedback capability is lost
Solution Approach 1:
The patent integrates capacitive sensing technology that continuously monitors hand position and deformation during exercises, providing real-time biofeedback to both patients and therapists. This feedback loop enables tracking of exercise performance, measurement of strength improvements, and verification of proper exercise form, directly addressing the information loss present in conventional devices.
4Reliability
If frequent therapist visits are required for monitoring, then patient care quality is maintained, but patient convenience and productivity deteriorate
Solution Approach 1:
The patent enables patients to perform self-monitored rehabilitation exercises using the device with built-in capacitive sensors that automatically track and record exercise performance. The device provides autonomous measurement and data collection capabilities, allowing patients to conduct rehabilitation sessions independently while maintaining reliable monitoring, thereby eliminating the need for frequent therapist visits.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate tracking of individual finger strength, improves patient accountability, and reduces the need for frequent therapist visits by providing measurable progress and compliance data.
Implementation Method 1
at least one capacitive sensor disposed on a surface of the at least one finger resistance device; measure a capacitance of the at least one capacitive sensor in real-time, wherein the capacitance is affected by a foreign object
Data Source
AI summary
A hand training device and corresponding method are used for sensing and measuring a capacitance corresponding to the pressure or force applied by the hand or fingers of the user. This hand training apparatus has slots for the index finger, the middle finger, the ring finger, and the pinky finger. The data obtained from the device can be utilized to create a 3-D model to indicate grip strength exerted by the hand or pinch strength.