Post on 23-Feb-2016
description
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MARS: A Muscle Activity Recognition System Enabling Self-configuring Musculoskeletal Sensor
Networks
IPSN 2013
NSLab study group 2013/06/17Presented by: Yu-Ting
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Outline
• Introduction• System Architecture• Evaluation• Conclusion
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Motivation
• Correct motion & prevent injury– Non-intrusive– Scalable (autonomous setup)– Accurate
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Disadvantage of Related Works
• Vision-based: LOS, clothing & skin cover• Needles: painful, low level activity• Larger sensors with contact gels:
low level activity
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Sensing of Muscles
• Accelerometer– Tremors & oscillations: 3.85 Hz ~ 8.8 Hz– Internal vibration: 10 Hz ~ 40 Hz
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System Overview
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Outline
• Introduction• System Architecture• Evaluation• Conclusion
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Sensor Node Network
• Provide error detection checksum• Anti-alias filter for the accelerometer• Wired to mobile data aggregator– SPI interface, 1Mbps– 10 Hr for 2200mAh battery
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Mobile Data Aggregator
• On Yellow Jacket board– Support 6 sensors & 2.5 meters
• Receive data from all nodes by TDMA• Decode checksum• Reasons of errors– Damaged sensors– Out of sync nodes
• Postpone data sampling until the next cycle
• Wi-Fi to backend server
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Backend Server – Muscle Activity Recognition
• 10Hz high pass filter: avoid signal from tremors• Feature extraction in Matlab using algorithms from WEKA
– 6 time domain features• RMS:
related to the intensity of an action• Cosine correlation:
relation of vibrations at different axes– 15 frequency domain features
• Apply DFT (Discrete Fourier Transform)• 3 information entropy of DFT magnitude• 3*4 bands PSD (Power Spectral Density)
– N sensors, M=21
• J48 decision tree classifier
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Backend Server – Motion Tracking & Visualization
• Complimentary filter fusion of sensor data– Obtain accurate orientations of the sensors– By quaternion-based complimentary filter [19,25]
• Range of motion limitation• Visualization and rendering– Java & Unity Gaming Engine
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Outline
• Introduction• System Architecture• Evaluation• Conclusion
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Vibration Signature Feature Ranking
• Muscle vibrations are directional• Current MARS assume the orientation of
sensors doesn't change• Future MARS will try to use polar coordinates
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Detection of Muscle Vibration
• PSD of accelerometer– Large difference in PSD– PSD is unique for different person
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User Study
• 4 females & 6 males from different background• Isolated and compound muscles• Compare three classfiers
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Precision & Recall
• Precision: positive predictive value• Recall: as sensitivity
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Result of User Study – Isolation Type
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Result of User Study – Compound Type
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Outline
• Introduction• System Architecture• Evaluation• Conclusion
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Conclusion
• Pros– Fine-grained muscle activity monitoring– Fast personalized system setup
• Sensors can be moved/changed afterwards– Real time processing with visualization
• Cons– Not convenient enough to wear the system– Need to be trained individually– The accuracy of the system may still vary with
placement
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Q&A