Behavior is ultimately the observable output of the nervous system. In many clinical situations, physicians rely on subjective behavior analysis to diagnose diseases or monitor their treatment. Likewise, during drug development for diseases affecting the nervous system, the measurement of behavioral outcomes is often crucial to determine the efficacy of a drug.
We have developed a system for behavioural analysis based on wearable miniaturized inertial sensors that can be used to evaluate humans and animals as small as laboratory mice (WEAR). These motions sensors provide multidimensional data that coupled with our optimized analyses algorithms enable us to quantify behaviour automatically, in an objective and unbiased way.
During this project we were able to optimize our motion sensors making them lighter and more efficient, and also developed a prototype that allows the acquisition of data from 4 motion sensors simultaneously, which can be used to obtain data from different body locations of the same individual or data from different individuals.
We have also progressed in the development of our analysis algorithms by acquiring more data in both clinical and pre-clinical contexts. In this regard we have collected data in a population of patients undergoing a nuclear medicine exam (DATScan) that is used for the diagnosis of Parkinson’s disease (PD), which allowed us to study the applicability of motion sensors in quantifying PD symptoms and predicting DATScan results. Moreover, we used our system to phenotype an animal model that develops progressive degeneration of dopamine neurons and thus presenting symptoms similar to PD. Our system not only was effective in tracking the development of the PD-like symptoms across time, but also uncovered new biomarkers for disease progression in this animal model.
Furthermore, we have partenered with Huse and developed our business case by compiling a document that analyses market potential, informs the value creation process, and devises an early business plan.
At the end of this project we conclude that the WEAR technology is a promising tool for automatic behaviour analysis, with a stronger position in the pre-clinical and basic neuroscience market where it can become the gold standard for motion assessment. The further development of this technology can have an important socioeconomic impact given its potential to empower discovery specially in pre-clinical pharmacological studies.
