A personalized body motion sensitive training system based on auditive feedback

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Hoelzl Gerold. A personalized body motion sensitive training system based on auditive feedback. Overview. Motivation System design Summary Future work. Motivation. Motivation. During training (jogging) it is fun to listening to music problem: - PowerPoint PPT Presentation

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Hoelzl Gerold

Overview

Motivation System design Summary Future work

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Motivation

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Motivation

During training (jogging) it is fun to listening to music problem:

rhythm of the music ≠ rhythm of the runner

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music rhythm (bpm) running rhythm

Hoelzl Gerold

Motivation

Idea adaptive selection of music according to the

running respectively the walking pace

additionally playing auditive status information like

heart rate speed, distance warnings if predefined limits are exceeded …

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System design

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System design

3 tasks movement analysis audio analysis mapping: movement<-> music

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System design Movement analysis

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[Scholich M., 1978, S.93]

acceleration maximum during heel- and toe ground contact g > 1,75 m/s²

recognition of a footstep: phase 7: „front support phase“phase 8,9: „rear support phase“

phase 7, 8 ,9 : „support phase“

[Larch R., 2001, S.3]

Hoelzl Gerold

System design Movement

acceleration values

extracted footsteps

distance calculation ->d(i)[ms]

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d(0)d(1)

d(2)d(3) d(4)

1

0

])[(1 n

i

msidn

mftFeature for classifying running rhythm defined as mean footsteptime (mft)

Hoelzl Gerold

System design

Audio analysis audio feature

beats per minute (bpm) (beat-tracking) recognized as a binary regular pulse

underlaying the music

separate calculation too computational intensive on mobile

devices stored as metadata

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System design

Mapping

O[bpm] = F(M,f[mft]) mapping function

M = {m1,…,mn} set of music piecesf[mft] feature

O[bpm] M set of fitting music pieces

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O = F(M,f)mft [ms]

feature f output O

music pieces [bpm]

Hoelzl Gerold

System design - Hardware

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System design

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System design

Hardware sensors

acceleration-sensor (movement analysis) ECG-sensor (biofeedback) GPS-sensor (speed, route, tracking)

communication technology Bluetooth

controller mobile phone (JavaME)

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System design Hardware (prototype)

acceleration-sensorSparkfun WiTilt v33-axis acceleration sensor with integrated Bluetooth capabilities

ECG-sensorPolar Heart Rate Monitor Interface +AMB2300-EV-Bluetooth-Board

GPS-sensor (integrated in mobile phone)

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System design - Software

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System design Software design

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Sensor-Controller

ECGSensor

Acceleration

Sensor

GPSSensor

Controller-

View

Audioplayer

Feature-calculation

Mappingmft<->bpm

Actors(pulse,

speed,..)

Hoelzl Gerold

System design

Software JavaME

API´s JSR 82: Bluetooth JSR 179: Location (GPS) JSR 135: Media (Audio, Video)

SonyEricsson JP8 current JavaME platform implementation

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Summary & Future work

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Summary

adaptive selection of music according to the running- respectively the walking pace

additionally playing auditive status information like

heart rate speed, distance warning if predefined limits are exceeded …

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Summary

Experimental results prototype showed high accuracy and

stability in both laboratory and naturalistic environments

short response time giving realtime “feeling”(~50ms)

Unexpected: crash of Bluetooth connections when built

in GPS sensor was used

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Summary

mapping function difficult to define one function for many

users music rhythm / speed is perceived very

subjective learning „on the fly“

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Summary

integrated sensors usage possible (less components) but restriction of device usage likely

(e.g. fixed position of acceleration sensor for movement analysis)

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Future work

support training programs in adaptively selecting forcing / retaining music pushing music if beneath a defined limit assuasive music if above a defined limit

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Future work

tracking with status information (using remote computer)

„control sportsman“ competitions (without borders)

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Questions?

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