Affective Man-Machine Interface: Unveiling human emotions through biosignals

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals

Factors influencing emergency delays in acute stroke management.

Early admission to hospital with minimum delay is a prerequisite for successful management of acute stroke. We sought to determine our local pre- and in-hospital factors influencing this delay. Time from onset of symptoms to admission (admission time) was prospectively documented during a 6-month period (December 2004 to May 2005) in patients consecutively admitted for an acute focal neurological deficit presented at arrival and of presumed vascular origin. Mode of transportation, patient's knowledge and correct recognition of stroke symptoms were assessed. Physicians contacted by the patients or their relatives were interviewed. The influence of referral patterns on in-hospital delays was further evaluated. Overall, 331 patients were included, 249 had an ischaemic and 37 a haemorrhagic stroke. Forty-five patients had a TIA with neurological symptoms subsiding within the first hours after admission. Median admission time was 3 hours 20 minutes. Transportation by ambulance significantly shortened admission delays in comparison with the patient's own means (HR 2.4, 95% CI 1.6-3.7). The only other factor associated with reduced delays was awareness of stroke (HR 1.9, 95% CI 1.3-2.9). Early in-hospital delays, specifically time to request CT-scan and time to call the neurologist, were shorter when the patient was referred by his family or to a lesser extent by an emergency physician than by the family physician (p < 0.04 and p < 0.01, respectively) and were shorter when he was transported by ambulance than by his own means (p < 0.01). Transportation by ambulance and referral by the patient or family significantly improved admission delays and early in-hospital management. Correct recognition of stroke symptoms further contributed to significant shortening of admission time. Educational programmes should take these findings into account