behaviour recognition base on smartphone's sensor

8/3/2019 Behaviour Recognition Base on Smartphone's Sensor

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THESIS REPORT

Behaviour recognition base on

smartphone's sensor

Student: Ngo Duy KienClass: K53CA

Supervisor: Bui The Duy



p y

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Content

I. Falling detection problem

II. Principle and method for system

III. Research progressIV. Format of the thesis

V. Research plan

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FALLING DETECTIONproblem

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Personal EmergencyResponse (PER) System

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1

Distinguishingbetween fallsand other types of normalbody

movement

2

Detecting a falland notifyingan emergencyserviceautomatically

3

Include acurrent locationfor cell phoneusing GPS or WIFI assisted

positioningsystem



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cce erome ersensor

- X-axis haspositive directiontoward the right side

of the device

- Y-axis haspositive direction

toward the top of the device

- Z-axis has

positive direction

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Principle and method for system

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Study of falls

77

q Falling Definition



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Study of falls

q Falling Types

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Study of falls

q Falling Types

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Study of non-falls

Non-falls



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Related Work

Real-Time Fall Detection based onShape and Motion Features



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Falling detection based onaccelerometer

q Analytical Method

§ Definition

§ Threshold

12

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Falling detection based onaccelerometer q Machine Learning

§ Identify natural clusters or groups of data contains

classified data and predicts the classes of unseen

data

§ Supervised Learning

§

Unsupervised Learning

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Machine Learning

Using a sliding window to transform thestream of acceleration data into instances for machine learning. The following attributeswere derived from the data within each 0.8second windows:

The average length of the acceleration vector within the window.

The average acceleration along the x, y,zaxes.



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RESEARCH PROGRESS

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Research progress

10/2011-11/2011:◦ Understood the problem

◦ Getting data and understood how

analysis data

12/2011- Now :

◦ Classification types of falls (oractivities daily living) with libsvm onweka

◦ 91%

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Format of the thesis

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Format of the thesis

1. Behavior problem and somepopular solution

2. Classification data with Machine

Learning

3. Implement system

4. Result and experiment

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Research plan

Finishing the classification withmachine learning

Compare the results with other

method to process data

Implement the system onSmartphone

Improving the implementation

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Thank you forlistening

2020

behaviour recognition base on smartphone's sensor

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