Biomechanical Analytics Platform for Real-Time Exoskeleton Control

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Solution Overview

Problem

Current robotic therapy systems for lower limb rehabilitation are limited in responsiveness to patient performance, requiring physical therapists to make operational adjustments based on difficult-to-quantify variables like fatigue and motivation, and lack rich feedback on biomechanical data for effective therapy planning and outcome prediction.

Innovation Solution

An integrated platform that includes a biosensing subsystem to collect biomechanical data, an analytics subsystem with neurocognitive and neuromechanical models for real-time analysis, and a control interface to adjust robotic exoskeletons, providing visual feedback and recommendations for therapy adjustments.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If physical therapists manually adjust robotic therapy systems based on patient performance, then therapy can be adapted to patient needs, but the system lacks real-time responsiveness and requires frequent therapist intervention

Engineering Contradiction:

Improvetherapy adaptationVSAvoidtherapist intervention frequency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system implements real-time feedback loops where sensors continuously monitor patient biomechanical data (joint angles, forces, muscle activation) and cognitive data (attention, effort), which is immediately processed by analytics subsystems to generate automated adjustments to robotic exoskeleton therapy parameters, eliminating delays associated with manual therapist assessment and adjustment

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The robotic therapy system performs self-adjustment of therapy parameters based on real-time analysis of patient performance data. The analytics subsystems automatically modify exoskeleton control parameters, resistance levels, and assistance forces without requiring therapist intervention, enabling the system to serve itself in adapting to patient needs

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If therapists manually assess patient fatigue and motivation, then therapy can be personalized, but difficult-to-quantify variables cannot be accurately measured

Engineering Contradiction:

Improvepersonalized therapyVSAvoidfatigue and motivation quantification

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The system replaces subjective therapist assessment of fatigue and motivation with objective sensor-based measurements. Biomechanical sensors measure muscle activation patterns, joint stiffness, and movement variability, while cognitive sensors (EEG, eye-tracking, GSR) directly measure neural and physiological indicators of attention and effort, converting intangible variables into quantifiable data

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system introduces intermediary sensor systems and analytics algorithms that mediate between the patient's internal states (fatigue, motivation) and the therapist's assessment. Sensors act as intermediaries to capture physiological signals, while analytics subsystems serve as intermediaries to interpret these signals and translate them into actionable therapy adjustments

Inventive Principle:

Principle #24Intermediary (Mediator)

3Device complexity

If limited biomechanical feedback is provided to therapists, then system complexity is reduced, but rich feedback data for therapy planning and outcome prediction is unavailable

Engineering Contradiction:

Improvefeedback system complexityVSAvoidbiomechanical data

Core Design Contradiction:

Device complexityVSLoss of information

Solution Approach 1:

The feedback system is segmented into multiple independent analytics subsystems, each processing specific types of data (biomechanical analysis, cognitive analysis, predictive outcome analysis). This modular architecture allows comprehensive data collection and processing while maintaining manageable system complexity through functional decomposition and specialized analysis modules

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS10532000B1Integrated platform to monitor and analyze individual progress in physical and cognitive tasks

Publication Date: 2020.01.14 HRL LAB

AI summary

Described is a system for online characterization of biomechanical and cognitive factors relevant to physical rehabilitation and training efforts. A biosensing subsystem senses biomechanical states of a user based on the output of sensors and generates a set of biomechanical data. The set of biomechanical data is transmitted in real-time to an analytics subsystem. The set of biomechanical data is analyzed by the analytics subsystem, and control guidance is sent through a real-time control interface to adjust the user's motions. In one aspect control guidance is sent to a robotic exoskeleton worn by the user to adjust the user's motions.