1. HUMANWARE - New Related Work - Activity and Location Recognition Using Wearable Sensors - Memories for Life - SharMe – Nokia Research Center La The Vinh Vinhlt-fit@mail.hut.edu.vn

2. Activity and Location Recognition Using Wearable Sensors Proposed by Seon-Woo Lee and Kenji Mase Using acceleration and angular velocity data Inexpensive, wearable sensors Determine user’s location base on relative distance from a given place Integrate incremental motion information over time

3. Activity and Location Recognition Using Wearable Sensors The system Linux-based PDA 2xSensor module Microcontroller Biaxial accelerometer Digital compass sensor Angular velocity sensor RS232 communication

4. Activity and Location Recognition Using Wearable Sensors

5. Unit motions Sitting Standing Walking - Steps Walking on a level ground Going up Going down

6. Activity and Location Recognition Using Wearable Sensors Training phase Record unit motions and heading measurements while user walks from one location to another A x (t),A z (t), θ(t) – Leg Module North, East, South, West – Waist Module Build the transition table

7. Activity and Location Recognition Using Wearable Sensors Recognition phase Detect walking behavior Construct the vector Match to the transition table Update user position

8. Activity and Location Recognition Using Wearable Sensors Motion Recognition σ x (t) σ y (t) σ θ (t) Δθ 1 Δθ 2 Δθ 3

9. Activity and Location Recognition Using Wearable Sensors Motion Recognition Sitting Standing

10. Activity and Location Recognition Using Wearable Sensors Steps Counting Using peaks of a z (t) – the blue

11. Activity and Location Recognition Using Wearable Sensors Moving position C x (k+1) = C x (k) + S l cos(2πA h ) C y (k+1) = C y (k) + S l sin(2πA h ) C z (k+1) = C z (k) + S s S l – Normalized length of a step on a level ground S s – Normalized length of an up/down step

12. Activity and Location Recognition Using Wearable Sensors Transition vectors from location i to j T i,j = {d x ij,d y ij,d z ij } Test condition |C x – d ij x | < threshold x |C y – d ij y | < threshold y |C z – d ij z | < threshold z

13. Activity and Location Recognition Using Wearable Sensors

15. Problems Accumulated error Limited in the case of long path Prone to drift