1. 1. Evaluation of a Context-Aware Applicationfor Mobile Robot Control Mediatedby Physiological Data: The ToBITas Case StudyBorja Gamecho1, Jos Guerreiro2, Ana Priscila Alves2, Andr Loureno2,Hugo Plcido da Silva2, Luis Gardeazabal1, Julio Abascal1, Ana L. N. Fred21 University of the Basque Country (UPV/EHU)Egokituz: Laboratory of HCI for Special Needs2 Instituto Superior Tcnico University of Lisbon (IST-UL)PIA: Pattern Image and Analisys Group
2. 2. 2/27Outline Motivation Research goals System description: What is ToBITas ? Evaluation: Usability study Conclusion
3. 3. Proliferation of Devices with Embedded Sensors3/27 Smartphones/Tablets A box with sensors Wearable Devices User activity and user emotional state recognitionWearables expands the sensing opportunities forsmartphone applications
4. 4. Take advantage of the growing ecosystem ofsensor devices Make it easier for developers to combine sensorsignals and new context discovery Support the generation of context-informationfrom the sensor data Enhance the interaction between users andmobile applications4/27Our Proposal
5. 5. Framework for Mobile Context Awareness5/27
6. 6. Example Application Using the Framework6/27MobileBITFrameworkBITALINO ROBOT CONTROL
7. 7. Research GoalsTesting the satisfaction and adaptation of users7/27to physiologically-enhanced sensors inputmethodsCreating an application based on low-cost sensorplatforms to extend the smartphone sensingcapabilities using a Context-Aware approachTesting the feasibility of the MobileBIT frameworkto create Context-Aware applications
8. 8. Context-Aware application to control a mobilerobotic platform using physiological sensors.8/27System Description
9. 9. 9/27Devices for ToBITas
10. 10. 10/27Devices for ToBITas Wirelessly operated mobile robotplatform Programmed using Arduino Bluetooth interface Receives commands from theSmartphone to move and use the clawBotn RollMobile RoboticPlatformRobot commands
11. 11. 11/27Devices for ToBITasBITalino SensorPlatformOptimized for real-time data streamingSampling Rates: 1, 10, 100, or 1000 HzBluetooth classic connectivitySensors Available:- EMG : Electromyography- ECG : Electrocardiography- EDA : ElectroDermal Activity- ACC : Accelerometer- LUX : PhotodiodeElectromyography - EMG Technique to measure the electricalactivity produced by the muscles 2 channels for TobitasAccelerometer ACC Device to measure g-force 1 axis (Z) for ToBITas
12. 12. 12/27Devices for ToBITasLG Optimus F5 Dual-Core 1.2 Ghz 1 GB RAM Bluetooth Communications Android 4.1.2SmartphoneAppFor ToBITas Application: Implements MobileBIT framework Manages Bluetooth connection withBITalino and Botn Roll Process data from sensors andtransforms into context-information
13. 13. 13/27Devices for ToBITasHuman Body:Right Arm
14. 14. Signal User Movement Context-Information Robot Command14/27EMG_1 The user folds his arm Action_detected:Right_arm_foldedMove ForwardEMG_2 The user closes hishandsAction_detected:Hand_ClosedOpen/Close the ClawACC Tilt the forearmPosition_detected:Forearm_upMove RightPosition_detected:Forearm_downMove LeftPosition_detected:Forearm_sideDont MoveRemote Control
15. 15. Data Processing Signals acquired at 100Hz Every context command is detected based on blocks of40 samples (with no overlapping) EMG signal data processing:15/27 ACC signal data processing: Low-pass filter implemented using a moving averageapproache1, e2,
16. 16. 16/27EMG SignalData over the threshold = Intentional Movement
17. 17. 17/27ACC SignalLEFT LEFT LEFTRIGHTCENTER
18. 18. 18/27MobileBIT FrameworkMobileBIT Framework
19. 19. 19/27Evaluation Usability Test: Quantitative and Qualitative Evaluate the adaptation of the user tophysiologically-enhanced sensor inputmethods 13 Participants (4 females) in 3 groups: Novices (x7): No prior experience Experienced (x4) : Have used EMG/ACC control before Experts (x2) : Involved in the develop and test of Tobitas
20. 20. 20/27Research Questions Are the users able to control our system ? Complete a task in a reasonable time Measure learning effect curve Do the users feel comfortable with this kind ofcontrol ? Complete the SUS test [Brooke 1996] Scores above 68 are considered above average[BROOKE 1996] - Brooke, J. (1996). "SUS: a "quick and dirty" usability scale".In P. W. Jordan, B. Thomas, B. A. Weerdmeester, & A. L. McClelland. UsabilityEvaluation in Industry. London: Taylor and Francis.
21. 21. 21/27Evaluation: Task DescriptionRepeat thetask threetimes
22. 22. 22/27Experimental Setup
23. 23. Experimental Results: QuantitativeTable 2. Summary of the task performance results for each group of participants(measured in seconds).23/27NovicesExperiencedExpertsAll160140120100806040200Attemp 1 Attemp 2 Attemp 3Novices (A)Experienced (B)Experts (C)All (A+B+C)Seconds
24. 24. 24/27Experimental Results: QuantitativeVisualization of all the trials for each groupNovices (A) Experienced (B) Experts (C)Seconds
25. 25. 25/27Experimental Results: SUS Scores Group A and Group B (11 participants) Average score: 73.86 A SUS score above a 68 would be considered above average and anything below 68 isbelow average. (http://www.measuringu.com/sus.php) 7 participants over 70 (63.6%) 5 from Group A and 2 from Group B 3 participants from 60 to 70 (27.3%) 1 from Group A and 2 from Group B 1 participant lower than 60 (9.1%) From group A: Lowest thresholds in the calibrationphase
26. 26. 26/27ConclusionAdaptation and satisfaction: Learning effect can be noticed: Adaptation After third run values are similar for group A and B A and B finished in reasonable time The time was 44% longer than the experts group The system is perceived as usable SUS score has been over 68 in averageSmartphone sensors have been extended usingthe BITalino sensor platformToBITas is a functional and usable Context-Aware application
27. 27. 27/27Future Work Exploratory study shows promising results More users are needed to reinforce our claims Flaws detected Three signals activate simultaneously: Arm folded Hand closed Arm position right Improved signal processing algorithms arerequired for fine tuning
28. 28. Experimental results and this presentation isavailable at :http://borjagamecho.info/tobitasEvaluation of a Context-Aware Applicationfor Mobile Robot Control Mediatedby Physiological Data: The ToBITas Case StudyBorja Gamecho1, Jos Guerreiro2, Ana Priscila Alves2, Andr Loureno2,Hugo Plcido da Silva2, Luis Gardeazabal1, Julio Abascal1, Ana L. N. Fred21 University of the Basque Country (UPV/EHU)Egokituz: Laboratory of HCI for Special Needs2 Instituto Superior Tcnico University of Lisbon (IST-UL)PIA: Pattern Image and Analisys Group