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Wearable Sensor Analysis for Gesture Recognition

Wearable Sensor Analysis for Gesture Recognition. Supervisor: Dr. Manolya Kavakli Student: Alexey Novoselov St. ID: 41650883. Agenda. 1: Background; 2: Goals; 3: Intended Outcomes; 4: Significance; 5: Approach; 6: Contemporary Technologies; 7: Piezo-Electric Technology;

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Wearable Sensor Analysis for Gesture Recognition

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  1. Wearable Sensor Analysis for Gesture Recognition Supervisor: Dr. Manolya Kavakli Student: Alexey Novoselov St. ID: 41650883

  2. Agenda 1: Background; 2: Goals; 3: Intended Outcomes; 4: Significance; 5: Approach; 6: Contemporary Technologies; 7: Piezo-Electric Technology; 8: Problems; 9: Experiments; 10: Output Data; 11: Initial Analysis; 12: Mathematical Approach; 13: Algorithmic Approach; 14: Conclusion 15: Future Work

  3. 1: Background • Virtual Reality is very promising scientific area; • Needs tools for interaction; • A lot of various technologies and devices; • Sensor Jacket is one of them; • No appropriate software for output analysis;

  4. 2: Goals • Investigate contemporary Motion Capture technologies and techniques; • Collect Sensor Jacket’s output data; • Analyze it; • Develop a mathematical model or an algorithm for Sensor Jacket;

  5. 3: Intended Outcomes • The list of justified experiments; • Data, collected during the set of experiments; • General characteristics of signals; • Application of mathematical approach; • Application of algorithmic approach; • Mathematical model or algorithm for signal processing;

  6. 4: Significance • Other Motion Capture systems not very convenient in use; • Sensor Jacket is wearable; • Sensor Jacket is simple; • But is has no software for output analysis;

  7. 5: Approach • Develop and perform experiments; • Collect data; • Filter data; • Analyze data; • Develop a tool;

  8. 6: Contemporary Technologies • Optical; • Inertial; • Mechanical;

  9. 7: Piezo-Electric Technology • Piezo-effect; • Piezo-electric sensor; • Made of graphite and silicone rubber;

  10. 8: Problems • Only static characteristic provided; • Electric noise in the output channels; • Strongly non-linear output signal; • Speed dependent;

  11. 9: Experiments

  12. 10: Output data

  13. 11: Initial Analysis • Minimal (Starting) value; • Maximal (Peak) value; • Steady Value; • The overshoot; • Difference between initial and final values;

  14. 12: Mathematical Approach • Basic characteristics; • Speed of the signal change; • Angle of slope of the signal; • Area of the signal;

  15. 13: Algorithmic Approach • Determine the active sensors; • Calculate the area of their signals; • Calculate the speed of sensors’ signals change; • Using the graphs (Figures 18-20), calculate the real speed of movement; • Using the tables of active sensors, determine to which types of movement (AoF, AoS, or AStF) this motion belongs; • Determine the approximate direction of movement; • Calculate the average time between the start and the peak of transient process for each group of sensors, forming the movement type; • Using the information from steps 4, 5, and 6, calculate the approximate distance that operator’s hand has passed during the motion in each direction; • Calculate the final coordinates of operator’s palm using formulas;

  16. 14: Conclusion • Technologies review; • Designed and performed experiments; • Collected, filtered, and analysed data; • Mathematical approach did not succeed; • Algorithm created;

  17. 15: Future Work • More experiments; • More sensitive data filtration; • Use advanced mathematical techniques; • Create more accurate and precise tool.

  18. Thank you! ?

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