Incentivization for Health Crowdsensing
Luis G. Jaimes, Robert JC Steele · 2017
Crowdsensing in the case of health-related information can enable a new mode of health data collection, able to collect more detailed and real-world health and physiological data than possible via traditional means. Various incentivization schemes for crowdsensing in general have been proposed, but there are characteristics specific to the health scenario that have been less well explored. Health crowdsensing can also be considered on a health condition-centric basis as 1) those with specific health conditions more often inherently collect data relevant to that condition; and 2) they are more motivated to see knowledge and research developments relevant to that condition and hence potentially more willing to take the steps needed to be a participant. In this paper we introduce a taxonomy of inventive mechanisms for health crowdsensing, and review the specific nature of incentivization for the case of health-related data. Finally, we present an incentive mechanism for collecting health-related data based on the well known best response dynamics in which participants have incomplete information on other participant's costs. A game theoretical multi-window framework is introduced where a stable solution is achieved after a number of iterations.