• Steven E Harte, Mainak Mitra, Eric A Ichesco, Megan E Halvorson, Daniel J Clauw, Albert J Shih, and Grant H Kruger.
• Department of Anesthesiology, Chronic Pain and Fatigue Research Center, University of Michigan Medical School, Ann Arbor, MI 48106, USA.
• Med Biol Eng Comput. 2013 Jun 1;51(6):633-44.

AbstractQuantitative sensory testing (QST) can provide useful information about the underlying mechanisms involved in chronic pain. However, currently available devices typically employed suffer from operator-dependent effects, or are too cumbersome for routine clinical care. This paper presents the design and initial validation of a novel automated pressure-pain type QST platform, termed the multi-modal automated sensory testing (MAST) system. The MAST configuration presented consists of wireless, hand-held thumbnail pressure stimulators (with circular 10 mm² rubber tips) and graphical touch screen interface devices to manage the QST process and obtain patient feedback. Validation testing of the custom-designed force sensor showed a 1 % error for low forces increasing to 2 % error for larger loads up to 100 N (full-scale). Validation of the controller using three ramp rates (64, 248, and 496 kPa/s) and six pressures (32, 62, 124, 273, 620, and 1116 kPa) showed an overall mean error of 1.7 % for applied stimuli. Clinical evaluation revealed decreased pressure pain thresholds in chronic pain patients (98.07 ± SE 16.34 kPa) compared to pain free, healthy control subjects (259.88 ± SE 33.54 kPa, p = 0.001). The MAST system is portable and produces accurate, repeatable stimulation profiles indicating potential for point-of-care applications.

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