Motoneurons are the final neural circuits that link the brain with skeletal muscles to enable the body to move. Impairments in the ability to regulate movement currently affect over 50 million Americans suffering from various neurological or musculoskeletal conditions. Yet the deficits in motoneuron control that underlie many of these conditions are difficult to discern because current research tools used to measure motoneuron activity from skeletal muscles are limited to needle electromyography (EMG) recordings, which are invasive, yield the firings of just a few motoneurons, and are only applicable to highly constrained muscle contractions. Although recently developed surface EMG techniques present a noninvasive alternative, current systems provide only gross measures of muscle activation with little to no information about the underlying motoneuron firings that comprise the signal. Advanced assessment tools are therefore needed to provide clinical researchers with measurements of underlying deficits in motoneuron control to better understand, evaluate, and treat disabilities that limit motor function. Our recent Phase II SBIR prototype is poised to meet this need. We have developed a unique, non-invasive, post-processing system that accurately measures the firing behavior of individual motoneurons from body-worn sensors during gait, exercise and activities of daily living. Through this Phase IIB SBIR, we now propose to advance our complex laboratory-based prototype into a turn-key, real- time NeuroMAP? system that meets versatility, usability and feasibility requirements for commercialization in the clinical research marketplace. We will integrate the existing multi-component system into a usable, wearable and mobile compatible system of wireless sensors with conformable skin-sensor interfaces to support use-cases across multiple muscles, movements, and clinical test procedures. The present post-processing software architecture will be redesigned with real-time algorithms, advanced user-interfaces and automated reporting of motoneuron measurements for intuitive, user-friendly operation. The usability and feasibility of our device will be tested among five leading clinical research partners across the fields of adult and pediatric neurology, physical therapy, sports rehabilitation and biomedical engineering. Through these efforts, and through strategic investments to support the regulatory strategy, manufacturing process and marketing plan from our industry partner, Delsys, Inc, we will deliver an impactful, usable and validated NeuroMAP? system ready for production, marketing and sales within 1 year of completing this award. 1

Public Health Relevance

The introduction of a non-invasive tool to measure motoneuron firings during clinically-based research assessments such as gait and activities of daily living, not otherwise possible, will enable clinical researchers to delineate the neural contributions to deficits or gains in muscle strength, dexterity, coordination, balance, and involuntary movements. This information can be used to design more directed care for reversing the effects of neurological damage or counteracting age-related deficiencies in muscle performance. Such evidence-based interventions would lead to more efficient allocation of health resources and improved mobility in people?s lives. 1

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
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Special Emphasis Panel (ZRG1)
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Gnadt, James W
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Altec, Inc.
United States
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Contessa, Paola; Letizi, John; De Luca, Gianluca et al. (2018) Contribution from motor unit firing adaptations and muscle coactivation during fatigue. J Neurophysiol 119:2186-2193
De Luca, Carlo J; Kline, Joshua C (2016) The common input notion, conceived and sustained by conjecture. J Neurophysiol 115:1079-80
Contessa, Paola; De Luca, Carlo J; Kline, Joshua C (2016) The compensatory interaction between motor unit firing behavior and muscle force during fatigue. J Neurophysiol 116:1579-1585
Kline, Joshua C; De Luca, Carlo J (2016) Synchronization of motor unit firings: an epiphenomenon of firing rate characteristics not common inputs. J Neurophysiol 115:178-92
De Luca, Carlo J; Nawab, S Hamid; Kline, Joshua C (2015) Clarification of methods used to validate surface EMG decomposition algorithms as described by Farina et al. (2014). J Appl Physiol (1985) 118:1084
De Luca, Carlo J; Chang, Shey-Sheen; Roy, Serge H et al. (2015) Decomposition of surface EMG signals from cyclic dynamic contractions. J Neurophysiol 113:1941-51
Kline, Joshua C; De Luca, Carlo J (2014) Error reduction in EMG signal decomposition. J Neurophysiol 112:2718-28
De Luca, Carlo J; Kline, Joshua C (2014) Statistically rigorous calculations do not support common input and long-term synchronization of motor-unit firings. J Neurophysiol 112:2729-44