Monitoring of Activity Levels of the Elderly in Home and Community Environments using Off the Shelf Cellular Handsets Progress Presentation by Martin Newell

Overview Project Outline Project Outline The System The System Testing Testing Sample of Results Sample of Results Analysis of Results Analysis of Results Progress To Date Progress To Date Remaining Work Remaining Work Additional Features Additional Features Questions Questions

Project Outline Primary Aims Primary Aims Test the application Test the application Detailed analysis of results Detailed analysis of results Test applications power consumption under various operation modes Test applications power consumption under various operation modes Develop and evaluate an algorithm to estimate additional parameters Develop and evaluate an algorithm to estimate additional parameters Implement and test the complete application Implement and test the complete application

The System Real time analysis of a subjects activity Real time analysis of a subjects activity Sample taken every 3 seconds Sample taken every 3 seconds Determines a subjects average step count and last step count Determines a subjects average step count and last step count If the subject stops the application returns zero If the subject stops the application returns zero Provides accurate and reliable information for medical professionals Provides accurate and reliable information for medical professionals Eliminates the need for a subject to note activity Eliminates the need for a subject to note activity Activity levels can be monitored remotely Activity levels can be monitored remotely

Testing Complete a thorough evaluation of the system Complete a thorough evaluation of the system A number of test subjects - 5 male and 5 female A number of test subjects - 5 male and 5 female Different walking speeds Different walking speeds Different handset types Different handset types Different position of handset on subject Different position of handset on subject Procedure Procedure Handset is connected via bluetooth to a laptop Handset is connected via bluetooth to a laptop Handset is placed on the subjects waist i.e. belt Handset is placed on the subjects waist i.e. belt Subject begins walking at the pace set by a metronome i.e. 120bpm, 90bpm Subject begins walking at the pace set by a metronome i.e. 120bpm, 90bpm Activity is recorded for a period of 60 seconds Activity is recorded for a period of 60 seconds

Sample of Results Here is a sample of the results taken from a 24 year old healthy male walking at a speed of 120 bpm on a flat surface Here is a sample of the results taken from a 24 year old healthy male walking at a speed of 120 bpm on a flat surface BlueCove version on winsock Create server by uri: btspp://localhost: f9b34fb;name=PCServerCO MM Waiting for connection... Walking Average_StepCount: 10 Last_StepCount: :55:50 Walking Average_StepCount: 10 Last_StepCount: :55:53 Walking Average_StepCount: 10 Last_StepCount: :55:56 Walking Average_StepCount: 10 Last_StepCount: :55:59

Analysis of Results After the first set of tests it was discovered that the handset didn’t recognize when the subject was walking up or down a set of stairs After the first set of tests it was discovered that the handset didn’t recognize when the subject was walking up or down a set of stairs Later testing revealed that the slower the subject was walking the more accurate the readings taken were Later testing revealed that the slower the subject was walking the more accurate the readings taken were Walking on a slope at the same pace as the flat also has no significant effect on the results - (maybe slope could be detected if a significant decrease in pace is discovered between samples) Walking on a slope at the same pace as the flat also has no significant effect on the results - (maybe slope could be detected if a significant decrease in pace is discovered between samples)

Progress To Date Testing has been carried out on 6 test subjects Testing has been carried out on 6 test subjects 5 males and 1 female - 4 females remaining 5 males and 1 female - 4 females remaining Testing at different walking speeds so far Testing at different walking speeds so far 60, 90, 120 and 130 bpm (beats per minute) 60, 90, 120 and 130 bpm (beats per minute) Testing on a slope Testing on a slope Testing on a stairs Testing on a stairs Brief analysis of results Brief analysis of results

Remaining Work Complete testing on 4 more female subjects Complete testing on 4 more female subjects Full analysis of the results Full analysis of the results Complete tests to evaluate the power consumption of the application in a number of different operational modes Complete tests to evaluate the power consumption of the application in a number of different operational modes A custom handset application will be needed for this A custom handset application will be needed for this Develop an algorithm to estimate additional parameters such as activity type, slope detection, fall detection. Develop an algorithm to estimate additional parameters such as activity type, slope detection, fall detection. Algorithm must be developed in matlab Algorithm must be developed in matlab Implementation of complete system including the power consumption algorithm and new features Implementation of complete system including the power consumption algorithm and new features

Additional Features May include - Long Term Gait Pattern Monitoring May include - Long Term Gait Pattern Monitoring Automated Fall Detection Automated Fall Detection Automated Exercise and Energy Expenditure Estimation Automated Exercise and Energy Expenditure Estimation Further development to detect if a subject is walking on a slope Further development to detect if a subject is walking on a slope Inclusion of GPS data to see surface types subject is walking on Inclusion of GPS data to see surface types subject is walking on

Questions??