Wearable EMG Text Input Using Binary Muscle Signal Mapping
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Solution Overview
Problem
Current input devices for text-based information communication, such as keyboards and microphones, require physical interaction and are external to the user, lacking a seamless and user-friendly method for conveying information through the body.
Innovation Solution
A wearable sensor configuration that detects muscle activity signals, converts them into binary signals, and translates these into textual information using mapping functions, allowing users to input text without external devices by moving their body parts, such as fingers, and transmitting this information wirelessly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If external input devices (keyboard, touchscreen, microphone) are used for text-based information input, then information input capability is achieved, but user convenience deteriorates due to requiring physical interaction and aiming at external devices
Solution Approach 1:
The system enables the user's own body to serve as the input device by detecting muscle activity signals directly from the user. The wearable sensor configuration detects muscle activity and converts it into digital information, allowing the user to input text without needing external keyboards, touchscreens, or microphones. This self-service approach eliminates the need to aim at or physically interact with separate input devices.
Solution Approach 2:
The patent replaces mechanical input systems (physical buttons, touchscreen contact) with a biological signal detection system. Instead of requiring mechanical interaction with external devices, the system uses sensors to detect electrical signals from muscle activity and converts them into digital information through mapping functions, substituting the mechanical input paradigm with a physiological signal-based paradigm.
2Ease of operation
If brain activity sensors (EEG) are used for text-based input, then text input capability is achieved, but reliability deteriorates because the technology is far from being ready for public use
Solution Approach 1:
The patent changes the physiological parameter being measured from brain activity (EEG) to muscle activity (EMG). Muscle activity sensors are aĉç technology with well-established signal processing methods, whereas brain activity sensors are still experimental. By switching to muscle activity detection and using binary signal classification (tensed vs. relaxed muscles), the system achieves reliable text-based input with currently available technology.
3Productivity
If continuous muscle activity signals are used for information input, then information input is achieved, but information quality deteriorates due to signal complexity
Solution Approach 1:
The system extracts only the essential binary state (tensed vs. relaxed) from the continuous muscle activity signal, discarding intermediate values and complex signal variations. This extraction of the core binary information simplifies the signal processing and improves information quality by focusing on the most meaningful distinction in muscle activity states.
Solution Approach 2:
The patent transforms continuous muscle activity signals into discrete binary signals through threshold-based classification. By changing the parameter representation from continuous amplitude values to discrete binary states (0 or 1), the system improves information quality and simplifies the mapping to textual information, making the input more reliable and easier to process.
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 reliable, simple, and accurate communication of information directly through the user's body, enhancing user experience by eliminating the need for physical input devices and improving information quality through binary signal detection and Morse code translation.
Implementation Method 1
the sensor unit is an electromyography sensor and the detected signals are electro potential signals
Data Source
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Figure 3a~3c
AI summary
The invention relates to a wearable sensor configuration (110) arranged to operate in a communications system (100; 100'), the wearable sensor configuration (110) comprises: - at least one sensor unit (115) being arranged to detect signals (S109) from muscle activity of a user; - a first electronic arrangement (101) being arranged to determine Internal Digital Information (IDI) on the basis of the detected signals (S109) by means of a first mapping function (1MF); - means (101, L110) being arranged to transmit the Internal Digital Information (IDI) to a second electronic device (102). The invention relates also to a communications system (100) and a method for communicating information in the communication system. The invention relates also to a computer program product comprising program code (P) for a computer (500) for implementing a method according to the invention.