1. Wearable Technologies for Assessment of Movement Disorder Graduate Students: Mark Hanson, Harry Powell, Adam Barth Faculty Advisors: Dr. John Lach, Dr. James Aylor TEMPO 1 TEMPO 2 Recent Publications M.A. Hanson, H.C. Powell Jr., J. Lach, “Teager Energy Assessment of Tremor Severity in Clinical Application of Wearable Inertial Sensors,” IEEE/NIH BISTI Life Science Systems and Applications Workshop, accepted for publication, 2007. H.C. Powell Jr., M.A. Hanson, J. Lach, “A Wearable Inertial Sensing Technology for Clinical Assessment of Tremor,” IEEE Biomedical Circuits and Systems Conference, accepted for publication, 2007. M.A. Hanson, J. Lach, “Assessing Joint Time-Frequency Methods in the Detection of Dysfunctional Movement,” Asilomar Conference on Signals, Systems, and Computers, 1870-1874, 2006 Charles L. Brown Department of Electrical and Computer Engineering Gait Classification Tremor Assessment Agitation Detection Research Description Normal Gait Tripping Gait Freezing Gait Quality of life is influenced by an individual’s ability to remain functionally independent A variety of movement disorders (e.g., Parkinson’s Disease, gait disorder, etc.) affect mobility and by extension, independence We believe that an information-centric, proactive approach to healthcare will facilitate research and better treatment of movement disorders, prolonging independence and improving quality of life in our aged population Currently, there exists no technology infrastructure to clinically study movement continuously, quantitatively, naturalistically, non-invasively, flexibly, and inexpensively Bandpass Filter Response Using Integer CoefficientsResponse of Bandpass Filters to Tremor Time-Series Data Teager Energy Analysis of Axial TremorTeager Energy Analysis of Deep Brain Stimulation Haar Wavelet Decomposition (A8) on Gait DataVariance Analysis of Power Spectral Density Time Domain Inertial Data of Gait ClassificationsShort-Time Power Spectrum of Gait Classifications Short-Time Fourier Spectrogram of Movement DataShort-Time Variance Analysis of Movement Data Short-Time Entropy Analysis of Movement DataShort-Time Cumulative Band-Limited Energy of Movement Data Data Acquisition Data Controller Destination Controller Wireless Transceiver S1S1 S2S2 SnSn D D DC C C FIFO Queue Physical Layer Link Layer Destination Controller Data Out Control Lines Data In DAQ S1S1 S2S2 SnSn Pattern Classification & Compression Feature Detection DSP Toolkit Data Controller Data Out Control Lines Queue Size Continuous, natural, inexpensive gait characterization enables improved fall risk assessment, including the detection of transient, abnormal gait events, which can motivate a therapeutic intervention for fall prevention Objective tremor measurement and classification, which has revealed elusive measures such as axial and ipsilateral benefit that facilitate the study of tremor presentation, treatment, and etiology Monitoring agitation/akathisia in neuroleptic pharmacotherapy patients enables improved therapeutic intervention TEMPO creates new opportunities for movement disorder research, including prevention, diagnosis, and therapy Example of Real-Time Signal Processing Using Sign-Correlation Instead of Cross Correlation System Architecture for TEMPO 3+ Technology Enabled Medical Precision Observation (TEMPO Example of Post-Processing of Tremor Data Using Fourier Analysis Our team has developed TEMPO, an end-to-end solution for objective assessment of movement disorder that addresses these deficiencies and allows physicians and medical researchers to 1) non-invasively record accurate, precise, quantitative human motion data via wearable wireless inertial sensors, and 2) process the data with sophisticated signal processing algorithms to reveal useful information not obvious or not accurately described by visual observation and self-report alone Our technology is currently deployed in three pilot studies with the University of Virginia and Carilion Health Systems