Personalized Electrical Muscle Stimulation via Digital Exertion Data
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Solution Overview
Problem
Existing electrical muscle stimulation (EMS) systems lack personalized electrical stimulation signals tailored to specific muscle groups, leading to inefficient time under tension and requiring professional supervision for effective muscle stimulation.
Innovation Solution
A system that captures digital exertion data from muscle groups during exercises and generates personalized electrical stimulation signals based on this data, allowing for automatic retrieval and distribution to other muscle groups, enabling effective muscle stimulation without professional supervision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standard waveforms are used for electrical muscle stimulation, then general purpose use is achieved, but the stimulation is not tailored to specific muscle groups resulting in inefficient time under tension
Solution Approach 1:
The system performs preliminary action by capturing and storing digital exertion data representing action potentials from each muscle group during exertion regimes before actual stimulation is needed. This pre-captured data serves as a template that can be automatically retrieved and applied during EMS sessions, eliminating the need for real-time professional analysis while maintaining personalized stimulation patterns specific to each muscle group's characteristics
Solution Approach 2:
The system creates copies of authentic action potential patterns captured from specific muscle groups and uses these digital copies to generate stimulation signals. Instead of requiring professionals to recreate stimulation patterns in real-time, the system stores digital representations of effective stimulation patterns and automatically retrieves and applies these copies during EMS sessions, ensuring consistent muscle-group-specific stimulation
2Productivity
If personalized electrical stimulation signals are generated for each muscle group, then time under tension is improved, but professional supervision is required increasing operational complexity
Solution Approach 1:
The system enables self-service by automatically retrieving stored digital exertion data and generating appropriate electrical stimulation signals without requiring professional supervision. The processing structure automatically matches the user's selection with pre-captured action potential patterns and generates personalized stimulation protocols, allowing users to independently receive optimized muscle stimulation that maintains high time under tension efficiency
Solution Approach 2:
The system incorporates feedback mechanisms by storing digital representations of actual muscle responses (action potentials) captured during exertion regimes. This feedback loop allows the system to learn and adapt to each muscle group's specific characteristics, automatically adjusting stimulation parameters based on previously captured performance data, thereby maintaining high productivity while enabling self-directed operation
3Reliability
If standard electrical stimulation signals are applied to disparate muscle groups, then device simplicity is maintained, but the nature of each muscle group's requirements is not considered reducing effectiveness
Solution Approach 1:
The system applies local quality by capturing and storing separate digital exertion data for each specific muscle group, recognizing that each muscle group has unique electrical characteristics and stimulation requirements. The processing structure retrieves and applies the specific action potential pattern corresponding to the target muscle group, ensuring that each muscle receives stimulation optimized for its local characteristics rather than a generic one-size-fits-all approach, thereby enhancing reliability of muscle stimulation
Data Source
AI summary
A system for electrically stimulating one or more muscle groups includes a processor-readable storage medium storing, in association with each of at least one muscle group, digital exertion data representative of one or more action potentials captured during an exertion regime from the muscle group of a respective subject; a signal generator for generating electrical stimulation signals; processing structure configured to automatically retrieve digital exertion data from the processor-readable storage medium and to automatically cause the signal generator to generate new electrical stimulation signals based on the digital exertion data; and a signal distributor for conveying the new electrical stimulation signals from the signal generator to one or more respective muscle groups of at least one different subject. Also provided is a system for providing exercise session data including a capture subsystem capturing one or more action potentials from at least one muscle group of a subject during an exertion regime, the capture subsystem including a processor-readable storage medium; processing structure generating digital exertion data representative of the one or more action potentials and creating the exercise session data by: storing the digital exertion data in association with an identification of the respective muscle group in the processor-readable storage medium; storing, in the processor-readable storage medium, one or more exercises each defining at least the digital exertion data for one or more muscle groups; and storing, in the processor-readable storage medium, one or more sessions each defining at least one or more of the exercises, a publishing subsystem for publishing the exercise session data for download and use by at least one different subject to cause another processing structure to generate and distribute new electrical stimulation signals to one or more respective muscle groups of the at least one different subject. Related methods are disclosed.