Wristband Proximity Sensing for Hands-Free Finger Force Estimation
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Solution Overview
Problem
Existing digital device control methods, such as smart phones and smart gloves, either immobilize the user's hands or obstruct their sense of touch, and electromyography (EMG) suffers from poor signal-to-noise ratio, high computational requirements, and sensitivity to sensor placement.
Innovation Solution
A wristband equipped with proximity sensors measures changes in wrist surface topography to estimate the force applied by fingers, using a neural network for accurate force estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a smartphone is used as a universal input device, then manufacturing time and resources are saved, but the user's hands are immobilized
Solution Approach 1:
The patent replaces traditional mechanical input devices (smartphones, keyboards) with a sensor-based system worn on the wrist. The proximity sensors detect finger proximity and force application through wrist surface topography changes, substituting mechanical interaction with optical/electromagnetic sensing, thereby freeing the hands while maintaining input capability
Solution Approach 2:
The wristband acts as an intermediary device between the user and the digital interface. Instead of directly holding a smartphone or pressing physical buttons, the user wears the wristband which senses finger movements and forces, translating them into digital commands. This intermediary approach saves manufacturing resources while preserving hand mobility
2Ease of operation
If smart gloves are used to sense finger presses, then hand movement is not obstructed, but the sense of touch is obstructed
Solution Approach 1:
The patent segments the sensing function from the hand itself and places it on the wrist. Instead of covering the fingers with conductive materials (smart gloves), the wristband contains proximity sensors that detect finger position and force indirectly through wrist surface changes. This segmentation preserves both hand movement freedom and tactile sensation
Solution Approach 2:
The wristband serves as an intermediary sensing device that detects finger interactions without contacting the fingers directly. By measuring wrist surface topography changes caused by finger force application, it provides tactile feedback information while leaving the hand's sense of touch unobstructed
3Measurement precision
If wrist-based EMG is used to estimate finger force, then force estimation is achieved, but signal-to-noise ratio is poor and computational requirements are high
Solution Approach 1:
The patent substitutes EMG (electrical signal measurement) with proximity sensing (optical/electromagnetic field measurement). Instead of detecting electrical activity from muscles which produces noisy signals requiring heavy computation, the system uses proximity sensors to detect wrist surface topography changes, yielding cleaner signals with lower computational processing requirements
Solution Approach 2:
The patent employs inexpensive proximity sensors (such as infrared or capacitive sensors) that can be easily manufactured and integrated into the wristband. These sensors provide sufficient measurement precision for force estimation without the high computational overhead of EMG processing, representing a cost-effective and computationally efficient solution
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 hands-free interaction by allowing users to apply force on any surface without obstructing hand movement or touch, providing accurate force estimation through advanced sensor technology.
Implementation Method 1
a group of at least two proximity sensors mounted on an inner surface of the wristband and configured to detect a proximity of each proximity sensor to a surface of a wrist
Data Source
AI summary
Devices, methods and computer programs for estimation of force applied by a finger based on wrist surface topography are disclosed. A computing unit (200A, 200B) receives, from a group of proximity sensors (300) mounted on an inner surface of a wristband (111) of a wrist apparatus (110A, 110b) communicatively connected to the computing unit (200A, 200B), a detected proximity of each proximity sensor (300) to a wrist surface of a user wearing the wristband. The computing unit (200A, 200B) measures changes in wrist surface topography based on the detected proximities, and estimates a force applied on a surface by at least one finger associated with the wrist based on the measured changes in the wrist surface topography.