Heart Rhythm Analysis by Sparse Representation for Immediate Acute Stressful Event Detection - The 63rd Annual Conference of the Israel Heart Society in association with the Israel Society of Cardiothoracic Surgery 12-13 April 2016, David Intercontinental Hotel, Tel-Aviv, Israel

Shai Tejman Yarden ^1,2 Leng Ky ³ Ofer Levi ⁴ Yisrael Parmet ⁴ Michael Saunders ⁵ Imanuel Lerman ⁶ Haim Berkenstadt ⁷ Yonina Eldar ⁸ Pavel Lifshits ⁸ James C Perry ² Dewleen G Baker ⁶ Tobias Moeller-Bertram ^3,6

¹Pediatric Cardiology, Sheba Medical Center, Ramat Gan
²Pediatric Cardiology, UCSD, CA
³Anesthesiology, UCSD, CA
⁴Department of Industrial Engineering and Management, Ben Gurion University
⁵Department of Industrial Engineering and Management, Stanford University, CA
⁶Center of Excellence for Stress and Mental Health, Veterans Affairs, CA
⁷Anesthesiology, Sheba Medical Center, CA
⁸The department of Electrical engineering, The Technion, Israel Institute of Technology, Haifa

Background: Heart rhythm analysis using sparse representation proved useful in detecting painful events. Our aim was to assess the heart rate in young healthy adult males who undergo a painful capsaicin injection for immediate detection of a stressful event, using the Fourier transform (FT), the Wavelet transform (WT) and the Orthogonal Matching Pursuit algorithm (OMP) with an over complete Fourier / Wavelet dictionary.

Methods: 16 volunteers participated in a study conducted in the pain clinic at a single center. All subjects were injected with intramuscular capsaicin while being monitored, pain was rated using the Visual Analogue Score.

Results: Data from 15 subjects were analyzed. Compared to baseline, The WT analysis showed a significant coefficients density increase during the initial 60 seconds of pain incline period (p<0.01) and at the 5 minute period (p<0.01). The OMP analysis showed a significant wavelet coefficients density increase during the initial 60 seconds (p<0.001) and at 5 minutes (p<0.001), both with suggestive higher amplitudes. Comparison of both methods showed that during baseline there was a significant reduction of wavelet coefficient density using the OMP algorithm (p<0.01), and a mean log amplitudes difference increase, correlating with the cold pressor test findings. Spectral analysis using the Fourier transform showed significant variations between the different subjects with various different patterns during pain.

Discussion: Heart rhythm analysis using novel methodologies proved feasible for immediate acute stressful event detection. Further computation and future studies are needed to assess real time detection in different clinical settings.