a practical approach to recognizing physical activities jonathan lester, tanzeem choudhury, and...
Post on 20-Dec-2015
224 views
TRANSCRIPT
![Page 1: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/1.jpg)
A Practical Approach to Recognizing Physical Activities
Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello
In Proceedings of the Fourth International Conference on Pervasive Computing (2006)
Benjamin Stokes, Presenter -- 1/24/11For CS 546: Intelligent Embedded Systems
![Page 2: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/2.jpg)
The Challenge
Personal activity recognition (in highly constrained use contexts)
• Healthcare sector: demand growing, currently relies on paid observer or self-reporting;
• Deficiencies: cost, accuracy, scope, coverage and obtrusiveness.
![Page 3: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/3.jpg)
Proposed Solution
To investigate three pressing constraints:
1. Unpredictable sensor location (wrist, waist, shoulder)
2. Minimal training across individuals
3. Cost (and sensor) minimizing
![Page 4: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/4.jpg)
Technical Preview
![Page 5: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/5.jpg)
Related Links
• MSP Research Initiative@ University of Washington & Intel Research Seattle: http://seattle.intel-research.net/MSP/
• Wiki for the Mobile Sensing Platformhttp://ubi.cs.washington.edu/wiki/index.php/Main_Page
• Jonathan Lester research page (with details on the Mobile Sensing Platform) http://www.cs.washington.edu/homes/jlester/research.html – Includes a great white paper on their MSP design justification and
experience
![Page 6: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/6.jpg)
Experimental Design
• 12 volunteers given a sequence of activities over several days (observer annotates true event)
• 8 different activities (sitting, standing, walking, walking up/down stairs, riding elevator, brushing teeth – selected as useful for elder care)
• Recognition trained & tested via activity classification algorithm developed earlier
![Page 7: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/7.jpg)
Technical Design
![Page 8: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/8.jpg)
Available Sensors
![Page 9: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/9.jpg)
Raw Data (12 hrs gathered)
(Data from 2nd Data Set)
![Page 10: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/10.jpg)
Data Preprocessing
18,000 samples of data per second so must summarize…
Result: 4 Hz @ 651 features
![Page 11: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/11.jpg)
Analysis Stage: Classification
Window: 15 second sliding (decreases error; reveals transitions) • with 5 second overlap
For each activity…•True activity type is observed by a human•All events of that type are divided into 4 “folds” (for training/testing, i.e., 3 :1)
![Page 12: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/12.jpg)
Investigating Sensor Location
Several options:1. Any location (of three) = ideal
…or…
2. Shoulder only3. Waist only4. Wrist only
![Page 13: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/13.jpg)
Learning Model
Often, learning models are either:a) discriminative: to learn the class boundaries without
regard for densitiesb) generative: to learn the class densities
…they have a mix. Specifically:1. Top 50 features as most discriminating (< 10%)2. To recognize activities, Hidden Markov Models
(HMMs – i.e., a simple Bayesian network); includes “temporal smoothing”
(Image Source: Wikipedia)
![Page 14: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/14.jpg)
Confusion Matrix (for the “location independent” condition)
Precision/recall
![Page 15: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/15.jpg)
Variation Across Users
• Can anyone benefit?• How much training?
Train on 1-12 users (folds 3:1), test on all 12
• Approaches 80% accuracy if testing on outsiders(approaches 95% accuracy if tested within group)
![Page 16: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/16.jpg)
Fewer sensors possible?
Which are most important?• Accelerometer (motion of user)• Audio (changing environment)• Barometric pressure (env.; in GPS for altitude)
Compare best sensor : top three (all locations)38.96% recall : 81.38%
…so use three!!
![Page 17: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/17.jpg)
Findings SummaryInvestigated…
(1) location sensitivity, Can recognize context within our constraints! (and works across locations)
(2) variations across users, Can be pre-trained by other individuals.
(3) which sensor modalities.Can use fewer & cheaper sensors.
![Page 18: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/18.jpg)
Critiques, Future Research• Curious: Defensive about dual analysis techniques?• Limitation: Excluded unclassified activities
(Overlooks 5 of 12 hours low ambiguity tolerance.)• Conceptual need: meta-classification to connect activities
(e.g., “making the rounds in hospital”)• Suggestion: Cluster population groups for performance.
(Here it was just “healthy individuals.”)• Suggestion: Consider time series data? (e.g., sitting
typically followed by standing, which precedes walking)
![Page 19: A Practical Approach to Recognizing Physical Activities Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello In Proceedings of the Fourth International](https://reader036.vdocuments.us/reader036/viewer/2022081515/56649d455503460f94a21cbc/html5/thumbnails/19.jpg)
Related Links
• MSP Research Initiative@ University of Washington & Intel Research Seattle: http://seattle.intel-research.net/MSP/
• Wiki for the Mobile Sensing Platformhttp://ubi.cs.washington.edu/wiki/index.php/Main_Page
• Jonathan Lester research page (with details on the Mobile Sensing Platform) http://www.cs.washington.edu/homes/jlester/research.html – Includes a great white paper on their MSP design justification and
experience