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Background: Current tools to measure pain are broadly subjective impressions of the impact of the nociceptive impulse felt by the patient. A direct measure of nociception may offer a more objective indicator. Specifically, movement-induced physiological responses to nociception may offer a useful way to monitor knee OA. In this proof-of-concept study, we evaluated whether integrated biomechanical and physiological sensor datasets could display linked and quantifiable information to a nociceptive stimulus. Method: Following ethical approval, we applied a quantified thermal pain stimulus to a volunteer during stationary standing in a gait lab setting. An inertial measurement unit (IMU) and an electromyography (EMG) lower body marker set were tested and integrated with ground reaction force (GRF) data collection. Galvanic skin response electrodes and skin thermal sensors were manually timestamp linked to the integrated system. Results: The integrated EMG, GRF and IMU data show fluctuations within 0.5 seconds of each other when a thermal pain trigger is applied at several time points during a stationary standing test. Manually timestamped physiology measures displayed increased values during testing for skin conductivity (up to 5 µSiemens, 37% compared to baseline) and skin temperature (up to 0.3˚C, 1% compared to baseline). Discussion: This proof-of-concept study suggests that physiological data mimics biomechanical data in response to a known pain stimuli. While this protocol requires further evaluation as to the measurement parameters, the association of the physiological output to the known pain stimulus suggests the potential development of wearable nociceptive sensors that can measure disease progression and treatment effectiveness.

Background: Current tools to measure pain are broadly subjective impressions of the impact of the nociceptive impulse felt by the patient. A direct measure of nociception may offer a more objective indicator. Specifically, movement-induced physiological responses to nociception may offer a useful way to monitor knee OA. In this proof-of-concept study, we evaluated whether integrated biomechanical and physiological sensor datasets could display linked and quantifiable information to a nociceptive stimulus. Method: Following ethical approval, we applied a quantified thermal pain stimulus to a volunteer during stationary standing in a gait lab setting. An inertial measurement unit (IMU) and an electromyography (EMG) lower body marker set were tested and integrated with ground reaction force (GRF) data collection. Galvanic skin response electrodes and skin thermal sensors were manually timestamp linked to the integrated system. Results: The integrated EMG, GRF and IMU data show fluctuations within 0.5 seconds of each other when a thermal pain trigger is applied at several time points during a stationary standing test. Manually timestamped physiology measures displayed increased values during testing for skin conductivity (up to 5 µSiemens, 37% compared to baseline) and skin temperature (up to 0.3˚C, 1% compared to baseline). Discussion: This proof-of-concept study suggests that physiological data mimics biomechanical data in response to a known pain stimuli. While this protocol requires further evaluation as to the measurement parameters, the association of the physiological output to the known pain stimulus suggests the potential development of wearable nociceptive sensors that can measure disease progression and treatment effectiveness.