Teleoperated FES Cycling System for Motor Recovery
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Solution Overview
Problem
Current rehabilitation technologies for neuromuscular disorders lack motivation and efficiency, particularly when used unsupervised, as they do not provide sufficient coordination between upper and lower limbs and fail to adapt to individual participant needs.
Innovation Solution
A bilateral teleoperation system that includes a master controller system driven by volitional efforts and a leg-cycle system driven by functional electric stimulation (FES) and a motor, with a controller that adjusts motor input and FES based on sensor input from the master controller, enabling coordinated upper and lower body movement and remote therapist control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If FES rehabilitation using a stationary cycle is used, then psychological benefits are achieved, but duration and efficiency are insufficient
Solution Approach 1:
The system incorporates a controller that receives sensor input from the master controller system and provides feedback to adjust motor input and FES application in real-time. This feedback mechanism allows the system to adapt to participant performance, maintaining engagement and psychological benefits while extending effective treatment duration through dynamic adjustment of stimulation and motor assistance.
Solution Approach 2:
The system uses a variable operator applied to motor input during FES cycles, transitioning between different levels of motor assistance and FES dominance. This dynamic adjustment allows the system to optimize both psychological engagement and treatment efficiency across different phases of rehabilitation, enabling longer effective treatment sessions.
2Reliability
If coordinated movement between upper limbs and lower limbs is added, then neural plasticity is improved, but device complexity increases
Solution Approach 1:
The system merges the master controller system (operated by the participant) with the leg-cycle system driven by FES and motor assistance. The controller integrates sensor input from both systems to coordinate upper and lower limb movements, achieving neural plasticity benefits through coordinated bilateral movement while consolidating control functions to manage complexity.
Solution Approach 2:
The controller acts as an intermediary that receives sensor input from both the master controller system and the leg-cycle system, processing this information to coordinate FES application and motor assistance. This intermediary function enables complex coordinated movement between upper and lower limbs while centralizing control logic to manage system complexity.
3Ease of operation
If rehabilitation is made available in the home environment, then accessibility is improved, but motivation decreases
Solution Approach 1:
The system incorporates real-time feedback mechanisms where the controller receives sensor input and adjusts FES and motor assistance accordingly. This feedback provides participants with a sense of control and progress even in unsupervised home use, maintaining motivation while enabling home-based accessibility.
Solution Approach 2:
The master controller system is driven by the participant's own volitional efforts, allowing them to self-regulate their rehabilitation sessions at home. The system responds to their inputs with coordinated FES and motor assistance, providing autonomous control that maintains motivation while enabling home-based accessibility.
4Adaptability or versatility
If a variable operator is applied to motor input during FES, then adaptability is improved, but control complexity increases
Solution Approach 1:
The system applies a variable operator to motor input that dynamically adjusts the level of motor assistance during FES cycles. This dynamic control allows the system to adapt to different phases of the rehabilitation cycle and participant needs, improving adaptability while using a unified control framework to manage complexity.
Solution Approach 2:
The variable operator modifies motor input parameters during FES application, adjusting the degree of motor assistance based on the phase of the FES cycle and participant performance. This parameter adjustment provides adaptability across different rehabilitation conditions while using a systematic approach to manage control complexity.
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
The system improves neural plasticity and motor recovery by providing coordinated and adaptable rehabilitation exercises, increases participant motivation through feedback and control over their rehabilitation, and allows for remote supervision and adjustment of therapy sessions.
Implementation Method 1
a leg-cycle system driven by both functional electric stimulation of a rehabilitation participant and the motor
Data Source
AI summary
Provided herein is a method, apparatus, and system for teleoperated, functional electric stimulation actuated rehabilitative cycling. Methods may include: receiving, at a master system, rotational input generating master system sensor input having a master system cadence; providing the master system sensor input including the master system cadence to a controller based on the rotational input from a rehabilitation participant or a remote therapist received at the master system; receiving, at a slave system, rotational input from the rehabilitation participant generating slave sensor input having a slave system cadence; providing the slave system sensor input including the slave system cadence to the controller based on the rotational input from the participant received at the slave system; and providing, from the controller, feedback through the master system in response to a difference between the master system cadence and the slave system cadence.