Inferences of physiological responses are seen increasingly in dynamically adaptive environments, towards personalization, learning, and interactive instructional design. In search of conclusive interpretations, scientists consider bio-sensing and physiological metrics in addition to formal assessment methodologies. Devices developed for laboratory use impose limitations that yield them prohibitively unsuitable for wider use due to their strong dependence on electrodes and kinetic restrictions. Additionally, synchronisation, diverse format and frequencies of data produced by assorted equipment, contribute to precision concerns. The development cited in this chapter circumvents the above constraints by using a proprietary real-time system. An algorithm assessing coinciding excitation of two important physiological quantities is used to evaluate classifiers indicative to focused attention and engagement. Experiments and interpretations are delineated, exposing system accuracy and potential to assist in substantiating propositions towards improved learning performance and adaptive personalisation.
A wearable chemical–electrophysiological hybrid biosensing system for real-time health and fitness monitoring