Design and Development of a Personal Trainer System Progress Presentation by Emer Bussmann

Introduction Exercise is the key to a healthy life importance of personal limits regulate and progress ability to measure, store and track the progress

The Design of the Proposed System maximum benefit out of training sessions 1) effective motion sensors for physical activity assessment 2) Bluetooth-based ECG circuitry 3) low cost portable acquisition system 4) software for monitoring and processing human body movement

SparkFun Board Bluetooth ECG sensors PDA equipped with LabVIEW for data processing PC-based Database Worn by User Bluetooth LabVIEW8 File Transfer Fig 3: Block Diagram of system

Accelerometer System micro-electromechanical device measure acceleration forces (static, dynamic) change in capacitance antero-posterior, medio-lateral, or vertical

Solution WiTilt v2.5 Board from SparkFun Electronics Freescale MMA7260Q triple-axis accelerometer and a class I Bluetooth link Internal antennae for range

Data acquisition Unit Acquire and process the signals LabVIEW software to filter, amplify, rectify and integrate to create clean noiseless output data Send data to a PC-based database

Solution Packard iPAQ hw6910/hw6915 Bluetooth type 1.2 and WiFi b Expansion: mini SD card

Mathematical Basis of the Parameters of Interest Stride Time Distance Speed Energy expenditure

Stride Time, Distance and hence Speed vertical bounce (of the hip) in an individual’s step is directly related to the person’s stride length

Step finding algorithm (zero crossing algorithm) An 8 point moving average is used to search for a maximum peak followed by a minimum

Determine the distance walked d : distance walked k : constant multiplier max : maximum acceleration value measured in this step min : minimum acceleration value measured in this step avg : average acceleration value for this step accel : represents all measured acceleration values for the step completed for each step

Energy expenditure 1) A low pass filter removes the shock noise of moving artefacts, 2) Activity x(t) at each axis is determined by integrating the accelerometer signal; where tau is set to 1s Total activity level is the Vector Magnitude (VM) of the signals; VM = x(t) + y(t) + z(t) 3) Every 10s the activity signals were summed

Vertical acceleration the predominant source of signal power 1) Step frequency is estimated using a count of samples between successive zero crossings in the vertical acceleration 2) Another filter is used to remove signals above twice the step frequency 3) VM is averaged at each speed and 4) Gait cycle is normalised to compare signals from different step frequencies

ECG System maintain a heart rate level that will optimise the effect of physical exercise use the design of a project from Sweden that is available in the public domain battery powered measuring up to 3 analogue channels of ECG on an exercising subject

Amp Microcontroller Bluetooth Module PDA With LabView Body Attached Sensors Analogue Signal UART Serial Connection Digital Signal Wireless Fig 7: ECG System

Schematic of ECG system

Progress to date All of the equipment has been ordered Extensive research Labview8 has been installed on laptop and currently testing signals from accelerometer

Future work January: Construct an ECG monitor February: Write software to process the accelerometer data March: Create a working system

Acknowledgements I would like to thank my supervisor Professor Gearóid Ó Laighin and PhD researcher Anthony Dalton for all their help and support.

References pt=abstract&list_uids= http:// pt=abstract&list_uids= … TA accelerometer 991AN_900.pdfhttp:// 991AN_900.pdf … pedometers using accelerometers pdfhttp://ieeexplore.ieee.org/Xplore/login.jsp?url=/iel5/10755/33900/ pdf … energy expenditure and accelerometers pdf?arnumber= http://ieeexplore.ieee.org/Xplore/login.jsp?url=/iel5/10646/33608/ pdf?arnumber= … energy expenditure and accelerometers … PDA … PDA 0B433?OpenDocument 0B433?OpenDocument … NI for LabVIEW … NI for LabVIEW … Sparkfun …Sparkfun