Biosensors and wearable sensor systems with transmitting capabilities are currently developed and used for the monitoring of health data, exercise activities, and other performance data. Unlike conventional approaches, these devices enable convenient, continuous, and/or unobtrusive monitoring of a user’s behavioral signals in real time. Examples include signals relative to hand movements and individual grip force data, which directly translate into spatiotemporal grip force profiles for the different measurement loci on the fingers and/or palm of the hand. Wearable sensor systems combine innovation in sensor design, electronics, data transmission, power management, and signal processing for statistical analysis, as will be shown in this presentation. The first part briefly summarizes current state of the art in grip force profiling to highlight important functional aspects. Then, wearable sensor technology in the form of sensor glove systems for the real-time monitoring of task skill evolution during training in a simulator task will be described on the basis of the spatiotemporal evolution of individual grip force profiles and their statistical and functional analysis. Although a lot of research is currently devoted to this area, many technological aspects still remain to be optimized, and new methods for data analysis and knowledge representation are urgently needed, as will be clarified in the discussion. Wearable sensor technology represents an open challenge for the scientific community and its further development partly relies on contributions from women researchers from multiple disciplines, as pointed out in the final conclusions of this presentation.