1. Dead Reckoning with Smart Phone Sensors for Emergency Rooms Ravi Pitapurapu, Ajay Gupta, Kurt Maly, Tameer Nadeem, Ramesh Govindarajulu, Sandip Godambe, and Arno Zaritsky Contact: maly@cs.odu.edu ICOST 2015 10th - 12th June 2015 Geneva

2. Outline Introduction and Background Lean and Spaghetti Diagram Indoor Positioning Systems Indoor Positioning System Challenges Dead Reckoning Algorithm Stride Detection Stride Length Estimation Change in User direction with each Stride Path Correction Summary ICOST 2015 10th - 12th June 2015 Geneva

3. Lean Lean is quality improvement philosophy process to maximize customer value and minimize waste Spaghetti Diagram Tracks user movement on floor Detect unnecessary or long paths Rearrange equipment New paths for optimal layout ICOST 2015 10th - 12th June 2015 Geneva

4. Current Indoor Positioning System GPS - becomes uncertain indoors Wi-Fi triangulation – high uncertainty RFID - costly Challenges Devise a cost effective system Devise a robust and accurate system Minimal impact on the infrastructure Shouldn’t hinder the activities of users at work place Solution System fuses smart phone sensors and other information such as Wi-Fi ICOST 2015 10th - 12th June 2015 Geneva

5. Dead Reckoning or Deduced Reckoning ‘Process of calculating one’s current position by using a previously determined or known position, and advancing that position based upon known or estimated measurements over elapsed time and course’. Sensors on a smart phone Accelerometer Gyroscope Dead Reckoning Algorithm Stride Detection Stride Length Estimation Change in user direction at each stride ICOST 2015 10th - 12th June 2015 Geneva

6. Stride Detection Accelerometer and Gyroscope data readings Accelerometer is very sensitive hence results in noisy data Basic signal processing to filter out noise ICOST 2015 10th - 12th June 2015 Geneva

7. Stride Detection continued.. Gyro scope readings are much smoother accounting for the slightest force exerted on the device Use accelerometer readings to validate gyro data for optimal decision making ICOST 2015 10th - 12th June 2015 Geneva

8. Stride Detection continued.. Processing the gyroscope readings to obtain a sinusoidal wave Use a Butterworth filter to smooth the data Processed gyro readings are fed to a Kalman filter to cancel noise The result is a smooth sinusoidal wave; use to infer the strides = distance between any two consecutive peaks ICOST 2015 10th - 12th June 2015 Geneva

9. Stride Length Estimation Personalized stride length model takes into account gait characteristics of an individual Stride patterns and lengths will be different for different individuals at different speeds General observation – slower walks smaller stride length and faster walks larger stride length Model function between time elapsed per stride and distance covered in stride by quadratic function Calibrate personalized approximation function by having a user walk at different speed fixed distances During operation: from stride detection obtain time elapsed for a stride, look up distance in approximation function ICOST 2015 10th - 12th June 2015 Geneva

12. Change in user direction with each stride Use quaternions to represent the orientation of phone in 3- D space using roll, pitch and yaw of the gyro scope The overall change in the users heading is calculated from the previous state using standard quaternion operations Path Correction Map representation - represent floor through its walls, doors, furniture and other obstacles to paths Error Detection –intersection of current path with obstacles such as walls ICOST 2015 10th - 12th June 2015 Geneva

13. Path correction - continued Error correction Corridor – path close to corridor segment then replace with corridor path Door – if path turns and close to door then replace with path through door Backtracking – if come to dead end, use back tracking to reverse prior decisions, e.g. instead of using door correction use corridor correction ICOST 2015 10th - 12th June 2015 Geneva

14. Backtracking correction

15. Results – CHKD emergency room path ICOST 2015 10th - 12th June 2015 Geneva Measured and corrected path at CHKD

16. Summary The overall objective was to lay a foundation for an accurate and robust indoor positioning system using inertial sensors on mobile phones With the measuring components unable to achieve correct paths we were able to achieve correct paths in all experiments at ODU and CHKD by adding path correction modules. Future work includes the addition of reporting modules that will allow the analyst to produce various plots selected from various users at various times and make that information available through the web to various devices. ICOST 2015 10th - 12th June 2015 Geneva

17. Stride Detection Continued.. Considering the phone is kept in pocket the forces which we measure are the pitch and the roll A step is considered the duration between the foot toes leaving the floor to the touchdown of the heel. The root mean square of pitch+roll is going to be the maximum when the user takes a step and when the stride continues on the other leg the pitch+roll value is the minimum. So we can infer a minimum followed by a maximum again followed by a minimum as two steps or a stride. Sampling threshold to avoid false steps (No two stirdes can happen in 30 samples) ICOST 2015 10th - 12th June 2015 Geneva