Evaluation of a Dynamic Time Warping matching function for human fall detection using structural vibrations Ramin Madarshahian, Doctoral Candidate, Juan M. Caicedo, Associate Professor Diego Arocha Zambrana, M.S. Candidate

Table of Content 2 DTW 3 Results 5 Introduction 1 Factorial analysis 4 Future work 6 Problem statement 2

3 1 Introduction Problem statement 2 DTW 3 Factorial analysis 4 Results 5 Future work 6 Importance of fall

Statistics: – Approximately one in every three adults 65 years old or older, falls each year [1,2] – Falls are the leading cause of injury deaths and accounted for 83% of all fatal falls in 2005 in Ireland [3] – annual cost of €10.8 m alone for just one Irish hospital [4] 4 1 Introduction Problem statement 2 DTW 3 Factorial analysis 4 Results 5 Future work 6 Importance of fall [1] A. Salva,and et all, 2004 [2] S.R.Lord,and et all, 2001 [3] [4] P.E. Cotter, 2006

Long lie! – Involuntarily remaining on the ground for an hour or more following a fall [1] – Half of those elderly who experience a ‘long-lie’ die within 6 months, even if no direct injury from the fall has occurred [2] 5 1 Introduction Problem statement 2 DTW 3 Factorial analysis 4 Results 5 Future work 6 Importance of fall [1] A.C. Reece, 1996 [2] D. Wild,and et all, 1981

Wearable devices Advantages: – Reliable algorithms – Cost efficient and not complicated to use Disadvantages – Sometimes it is hard to use – Easy to forget to use, specially for Alzheimer patients 6 1 Introduction Problem statement 2 DTW 3 Factorial analysis 4 Results 5 Future work 6 Importance of fall [1] Daniel Rodríguez-Martín, 2013 fall detection systems [1]

7 1 Introduction Problem statement 2 DTW 3 Factorial analysis 4 Results 5 Future work 6 Importance of fall [1] Philippe Katz, and et al, 2013 fall detection systems Vision based methods Advantages: – Independent of elderly Disadvantages – Privacy concern – Blind point [1]

8 1 Introduction Problem statement 2 DTW 3 Factorial analysis 4 Results 5 Future work 6 Importance of fall [1] Diego Arocha, and et al, 2014 fall detection systems Vibration based methods Advantages: – Independent of elderly – Cost efficient – High sensitivity Disadvantages – More work is needed to develop algorithms with less number of false alarms [1]

An experiment designed to consider effect of three different factors on recorded signal: – Type of object dropped – Height of the fall – Distance to the sensor Goal: to see which factor is the most effective. 9 Introduction 12 Problem statement DTW 3 Factorial analysis 4 Results 5 Future work 6 objective

10 Introduction 12 Problem statement DTW 3 Factorial analysis 4 Results 5 Future work 6 objective Experiment Factor Distance Factor Height Factor Type

11 Introduction 12 Problem statement DTW 3 Factorial analysis 4 Results 5 Future work 6 objective Experiment Signal database

12 Introduction 12 Problem statement DTW 3 Factorial analysis 4 Results 5 Future work 6 objective Experiment Signal database

13 Introduction 12 Problem statement DTW 3 Factorial analysis 4 Results 5 Future work 6 objective Experiment Signal database Calibration signals

14 Introduction 1 Problem statement 23 DTW Factorial analysis 4 Results 5 Future work 6 Theory (Example)

15 Introduction 1 Problem statement 23 DTW Factorial analysis 4 Results 5 Future work 6 15 DTW= DTW= Theory (Example)

16 Introduction 1 Problem statement 23 DTW Factorial analysis 4 Results 5 Future work 6 16 Factors RunheightTypedistanceMeanMedian Standard deviation 1highbagclose lowbagclose highballclose lowballclose highbagfar lowbagfar highballfar lowballfar Theory (Example) Results

Introduction 1 Problem statement 2 DTW 34 Factorial analysis Results 5 Future work 6 Theory-Normal Plot a case study for optimizing a product life: [1] [1] Jiju Antony, 2013

Introduction 1 Problem statement 2 DTW 34 Factorial analysis Results 5 Future work 6 Theory-Normal Plot [1] Jiju Antony, 2013 Factors and Levels In our experiment we have 3 factors: 1-Height Low and High 2-Type Basketball and Bag of K-Nex 3-Distanse Far to the sensor and Close to the sensor

Introduction 1 Problem statement 2 DTW 34 Factorial analysis Results 5 Future work 6 Theory-Normal Plot [1] Jiju Antony, 2013 Box-Cox transform Checking assumption

Introduction 1 Problem statement 2 DTW 34 Factorial analysis Results 5 Future work 6 Theory-Normal Plot [1] Jiju Antony, 2013 Box-Cox transform

Introduction 1 Problem statement 2 DTW 34 Factorial analysis Results 5 Future work 6 Theory-Normal Plot [1] Jiju Antony, 2013 Box-Cox transform

22 Introduction 1 Problem statement 2 DTW 3 Factorial analysis 45 Results Future work 6 Bag Basketball

23 Introduction 1 Problem statement 2 DTW 3 Factorial analysis 45 Results Future work 6 Significant factor

24 Introduction 1 Problem statement 2 DTW 3 Factorial analysis 45 Results Future work 6 1-DTW can be used successfully for comparison of fall signals. 2-To perform a good factorial analysis logarithm transform on response obtained from DTW is recommended. 3-Factorial analysis shows that in compare to height of fall and distance of fall place to sensor, Type of falling object has most significant impact on response.

25 Introduction 1 Problem statement 2 DTW 3 Factorial analysis 4 Results 56 Future work 1-DTW is one of the scales for comparison of signals, other methods of signal comparison can be evaluated using factorial analysis. 2-DTW can be applied using different type of distance matrix. Study of these function is useful to extract the best response. 3-Development of a prediction algorithm using DTW is our next research step in this project.

Evaluation of a Dynamic Time Warping matching function for human fall detection using structural vibrations Ramin Madarshahian, Doctoral Candidate, Juan M. Caicedo, Associate Professor Diego Arocha Zambrana, M.S. Candidate Thanks!