http://ase.iha.dk/Default.aspx?ID=9944

Quantitative Comparison Quantitative Comparison of the Accuracy Between of the Accuracy Between the OLAM Continuous-the OLAM Continuous-

Tracking Device and Tracking Device and Commercial MonitoringCommercial Monitoring

Shannon Cahill-WeisserShannon Cahill-WeisserMentor: Dr. Patrick ChiangMentor: Dr. Patrick Chiang

Department of Electrical Engineering Department of Electrical Engineering and Computer Scienceand Computer Science

Oregon State UniversityOregon State University

Why Make Vital Signs Monitors Wearable?

One third of physicians make decisions with incomplete information. [1]

In General...

• Assists diagnosis/prognosis

• Can indicate specific events

• Promotes patient independence [2]

[1] PricewaterhouseCoopers’ Health Research Institute, 2011[2] Hayes, et al., 2008

Based on PricewaterhouseCoopers Health Research Institute Physician Survey, 2010

Why Make Vital Signs Monitors Wearable?

Specific Examples...Activity:

• Energy expenditure [1]

• Gait velocity to predict

cognitive impairment [2]

Electrocardiogram: 2006: 36.3% of Americans have heart disease [3]

Contextual vs. clinical measurement

[1] Chen et. al., 2005[2] Buracchio et. al., 2010 [3] CDC, 2009

Linus Pauling Institute Collaboration

•OLAM worn to study effects of micronutrient

•Worn by 10 subjects in an 6 week trial

•Study conducted with lab of Dr. Tory Hagen

Albright, Goska, Hagen, Chi, Cauwenberghs, and Chiang EMBS Conference, 2011

Project Plan Objective:

Evaluate performance of ECG against pulse oximeter

Compare activity data to commercial monitor data

Apply analysis to LPI study data

Hypothesis: Activity data will be comparable to commercial sensing.

ECG data will contain motion artifact.

Considerations for Any Wearable Monitor

Biocompatibility

Durability

Efficiency

Data Quality Signal to noise ratio Particularly motion induced artefactParticularly motion induced artefact

Considerations for the OLAM

[1] Albright, Goska, Hagen, Chi, Cauwenberghs, and Chiang EMBS Conference, 2011[2] http://www.theactigraph.com/products/gt3x-plus/[3] http://www.theactigraph.com/products/actitrainer/

OLAM [1] GT3X+ [2] ActiTrainer [3]

Sensor Variety ECG, accelerometer, gyroscope

Accelerometer,light sensor

ECG accessory, accelerometer, light sensor

Battery Life 15 days min. 31 days 7-14 days

Memory 2 GB 512 MB 4 MB

Rate/Sensitivity 100 Hz/ ±2-8 g 30-100 Hz/ ±6g 30 Hz/ ±3g

Mounting Over or under Chest belt Polar heart strap

Capacitive ECGSensor

Capacitive ECGSensor

3-D ADXL345 MEMS

Accelerometer

3-D ADXL345 MEMS

Accelerometer

100 Hz Sampling,5 sec per

minute

100 Hz Sampling,5 sec per

minute

MATLABMATLAB2.5 Hz Low Pass Filter0.25 Hz High Pass Filter2.5 Hz Low Pass Filter

0.25 Hz High Pass Filter

Obtain and compare counts over minutes and hours

Obtain and compare counts over minutes and hours

Sampling and Analysis Block Diagram

Albright, Goska, Hagen, Chi, Cauwenberghs, and Chiang EMBS Conference, 2011

Counting Method

1. Average accelerometer magnitudes over number of samples. These are “counts”.

2. Add counts for desired time period.

3. Analysis code written to “window” continuous GT3X+ data.

SAMPLINGSAMPLING SAMPLINGSAMPLING

sleepsleepsleepsleep

5 sec

54.5 sec

Albright, Goska, Hagen, Chi, Cauwenberghs, and Chiang EMBS Conference, 2011

  Hour Counts Minute Counts

μ Difference (%), Unfiltered 6.92 7.84

σ Difference (%),  Unfiltered 4.00 3.52

μ Difference (%), Filtered 5.67 315.79

σ Difference  (%)  Filtered 5.05 1072.05

• Agreement good in unfiltered and hourly data• Error high in filtered minute data• Sources: reaction time, window matching, extrapolation

on bench on bench

Stationary

Walking

Working at Computer

Heart Rate Data

Taped to Skin In Belt Over Shirt

Heart Data

• Compared to Crucial Medical Systems pulse oximeter

• Avg. Difference: 9.0 bpm, Stdev: 4.5 bpm

• Indicates higher sensitivity to cycling

OLAM Pulse Ox. Absolute Difference

72 77 5.0

72 77 5.0

72 82 10.

72 88 16.

96 87 9.0

[1] http://www.crucialmedicalsystems.com/oled-cms50c-fingertip-pulse-oximeter-and-oxygen-meter-p-220.html

[1]

Conclusions

1. Duty-cycled activity data agrees highly with commercial data on an hourly scale.

2. Heart data is more sensitive to duty-cycle length.

3. Further post-processing is necessary to obtain accurate heart-rate data.

References

“Healthcare Unwired: New Business Models Delivering Care Anywhere” [Online], PricewaterhouseCoopers’ Health Research Institute, 2010, Available at: http://www.lindsayresnick.com/Resource_Links/Healthcare_Unwired.pdf, Accessed Sept 12, 2011.

T. Buracchio, H.H. Dodge, D. Howieson, D. Wasserman, and J. Kaye, "The Trajectory of Gait Speed Preceding Mild Cognitive Impairment", Arch Neurol., 2010; 67(8):980-986.

T. Hayes, M. Pavel, and J. Kaye, "An Approach for Deriving Continuous Health Assessment Indicators from In-Home Sensor Data" in Selected Papers from the 2007 International Conference on Technology and Aging , IOS Press, Amsterdam, Netherlands, 2008.

US Census Bureau, State & County Quickfacts [Online], Available from: (http://quickfacts.census.gov/qfd/states/00000.html , Accessed: Feb. 24, 2011.

American Heart Association, American Heart Disease and Stroke Statistics―2009 Update At-A-Glance (http://www.americanheart.org/presenter.jhtml?identifier=3037327), Accessed Feb. 24, 2011.

R.K. Albright, B.J. Goska, T.M. Hagen, M.Y. Chi, G. Cauwenberghs, and P. Y. Chiang, “OLAM: A Wearable, Non-Contact Sensor for Continuous Heart-Rate and Activity Monitoring,” accepted, IEEE Engineering in Medicine and Biology Conference, 2011.

ActiGraph, ActiTrainer Activity Monitor [Online], Available at: http://www.theactigraph.com/products/actitrainer/. Accessed: Sept 12, 2011.

ActiGraph, ActiGraph GT3X+ Monitor [Online], Available at: www.theactigraph.com/wp-content/uploads/ActiGraphCT3X+Specs.pdf, Accessed: Sept, 2011.

K.Y. Chen, and D.R. Bassett, Jr., “The Technology of Accelerometry-Based Activity Monitors: Current and Future,” Medicine & Science in Sports & Exercise, American College of Sports Medicine, Indianapolis, IN, pp. S490-S500, 2005.

Bonomi, A. G. Bonomi and K. R. , “Advances in physical activity monitoring and lifestyle interventions in obesity: a review.”, International Journal of Obesity, 1-11, 2011.

MORE UPON REQUEST

Acknowledgements

• HHMI and URISC

• Dr. Patrick Chiang

• Dr. Stewart Trost

• Ben Goska, Ryan Albright, Samuel House, Sean Connell, Daniel Austin, and Robert Pawlowski

• The lab of Dr. Tory Hagen