At the Hansma Lab, we began by exploring the use of home-use Electroencephologram, EEG, for chronic pain recovery. We went on to explore many other home-use biofeedback possibilities including Electromyography, EMG, Electrocardiogram, ECG, Photoplethysmography, PPG (at various body sites including finger, earlobe, temple, forehead, carotid artery, top wrist and bottom wrist), Galvanic Skin Response, GSR, Skin Conductance, Temperature (at various body sites including finger, palm, wrist, forehead, carotid artery, basilar artery, top wrist, and bottom wrist), Motion (with multi-axis accelerometers and gyroscopes on head, hands and wrists), majority of our biofeedback devices so far have explored increasing users’ hand temperature.

We attempted to use these biofeedback sensors with chronic pain subjects as a part of a chronic pain recovery program. We gradually eliminated sensors that were more aggravating or inconvenient than useful. Specifically, we ended up eliminating, for home-use biofeedback, any sensors that needed electrodes on the body because they did not show enough advantage over sensors without electrodes.

A subset of over 20 sensors without electrodes, including temperature, Photoplethysmography, PPG and motion sensors at various body locations was then used to attempt to quantify chronic pain. This resulted in one conference publication* and one accepted manuscript**. Based on these results we have narrowed our research focus to the two most promising sensors: finger or hand temperature and PPG.

 Chronic pain is associated with an activated “fight or flight” response in individuals, which has been shown to reduce blood–and heat–from the extremities. As users increase their hand temperature, the “fight or flight” response lessens. To show changes in temperature and provide intuitive feedback on progress, our biofeedback devices cycle through the spectrum of colors.

We have used these hand temperature biofeedback devices with many individual subjects and in one chronic pain recovery workshop.

In addition to temperature biofeedback, the Hansma Lab has been exploring heart rate variability measured with Photoplethysmography, PPG, in our most recent study (Summer 2022).

We are especially interested in using a new technique, Dynamic Phase Extraction***, to provide both the magnitude and phase of the pulse variations relative to a breath pacer. We have some preliminary indications that the phase may be useful for biofeedback for chronic pain.

*Zhao, Y., Ly, F., Hong, Q., Cheng, Z., Santander, T., Yang, H.T., Hansma, P.K. and Petzold, L., 2020, November. How much does it hurt: A deep learning framework for chronic pain score assessment. In 2020 International Conference on Data Mining Workshops (ICDMW) (pp. 651-660). IEEE.

**Zhuowei Chenga, *, Franklin Lyb, Tyler Santanderc, Elyes Turkid, Yun Zhaoa, Jamie Yooc, Kian Lonerganc, Jordan Grayc, Christopher H. Lid, Henry Yangb, Michael Millerc, Paul Hansmad, Linda Petzolda,b Preliminary Study: Quantification of Chronic Pain from Physiological Data, accepted for publication in Pain Reports.

***Li, C.H., Ly, F.S., Woodhouse, K., Chen, J., Cheng, Z., Santander, T., Ashar, N., Turki, E., Yang, H.T., Miller, M. and Petzold, L., 2022. Dynamic Phase Extraction: Applications in Pulse Rate Variability. Applied Psychophysiology and Biofeedback, 47(3), pp.213-222.