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Intelligent Biomechanical Machines

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by

Ed Lemaire

on 7 March 2014

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Transcript of Intelligent Biomechanical Machines

Intelligent
Biomechanical Machines
Input
Output
External - Senses
Internal - Muscle Sensors, etc.
in·tel·li·gent : adjective

(of a device, machine, or building) Able to vary its state or action in response to varying situations, varying requirements, and past experience
What do I want to do?
How do I want to do it?
When do I want to do it?
Why can't I do it?
Decision
Walk, run
Sit
Climb
Grasp
Throw
Stop
Recover
Fast or slow
Powerfully?
Accurately
Safely
Right now
After completing another movement
Before falling
Traffic
Too slippery
Cannot be done safely
Not enough power
Orthotics
Are you
weightbearing?
Is your knee
straight?
Is your knee
flexing too fast?
Prosthetics
Do I need a
stiffer knee?
Should my ankle
plantarflex?
How should I
grip?
Small, low power sensors are available
Batteries are improving (smaller, more power)
Smaller, cost effective, motors are evolving
Control software is improving
People are using these devices ... providing information to improve performance
Weight (comparator can be a piece of plastic)
Noise (motors, gears, etc.)
Maximum force
Size
Cost
How do we deal with
these issues?

Walking Frame - Exoskeleton - Powered Orthotics
Self supporting
Can use heavier components
Bigger battery
More stable
More complex
Portable?
Greater moments?
More speed
Joystick
How do we control the robot?
Control Panel
EMG + Sensors
Select an activity and the robot moves the body based on predetermined settings. Timing based on load, limb/body motion, or tilt angle
Docking Station
Assistive Docking Device
Use intelligent passive device for daily activity
Dock to powered device as needed
Fast and easy setup required
Use for stairs, lifting, yard work,
Workplace
Fast donning and doffing is essential
Orthotic principles and engineering
Can we meet the
17 second challenge
?
Integrated into device
Wireless communication
Reporting software
Intelligent analysis
Identify device problems
Identify user changes
Integrated Outcome Measures
Wearable Sensors / Phones
Sensor Environments
Existing Sensors
Usage and activity reports
Vendors control access
Who owns data stored in an assistive device?
End user? Company? Clinical facility?
Access to the Data
Quick Capture
Instant Reports
Generated automatically after data collection
Formatted for easy clinical interpretation
Specific to patient classification
Data to information to clinical decision
Use the information to change practice!
The Prosthetic Data Challenge
To companies with sensor controlled devices
Open source data from endusers (i.e., share)
De-identified data and activity
Provide enough data for complex analyses (neural networks, etc.)
Move to the next generation of control !
The Device Decision Challenge
Setup data collection within minutes, or seconds

Immediate reports

Automatic error checking
Good data quality

Application-specific reporting

Provide knowledge for clinician and feedback for client
The Data - Knowledge Challenge
Use Outcome Measures in Practice
The Orthotist Learning
Challenge
Assist
Full transcript