by Keyword: Motivation
Vouloutsi, Vasiliki, Verschure, P., (2018). Emotions and self-regulation Living Machines: A Handbook of Research in Biomimetic and Biohybrid Systems (ed. Prescott, T. J., Lepora, Nathan, Verschure, P.), Oxford Scholarship (Oxford, UK) , 327-337
This chapter takes the view that emotions of living machines can be seen from the perspective of self-regulation and appraisal. We will first look at the pragmatic needs to endow machines with emotions and subsequently describe some of the historical background of the science of emotions and its different interpretations and links to affective neuroscience. Subsequently, we argue that emotions can be cast in terms of self-regulation where they provide for a descriptor of the state of the homeostatic processes that maintain the relationship between the agent and its internal and external environment. We augment the notion of homeostasis with that of allostasis which signifies a change from stability through a fixed equilibrium to stability through continuous change. The chapter shows how this view can be used to create complex living machines where emotions are anchored in the need fulfillment of the agent, in this case considering both utilitarian and epistemic needs.
JTD Keywords: Emotion, Motivation, Needs, Appraisal, Self-regulation, Homeostasis, Allostasis, Human–robot interaction, James–Lange theory
Antelis, J.M., Montesano, L., Giralt, X., Casals, A., Minguez, J., (2012). Detection of movements with attention or distraction to the motor task during robot-assisted passive movements of the upper limb Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 6410-6413
Robot-assisted rehabilitation therapies usually focus on physical aspects rather than on cognitive factors. However, cognitive aspects such as attention, motivation, and engagement play a critical role in motor learning and thus influence the long-term success of rehabilitation programs. This paper studies motor-related EEG activity during the execution of robot-assisted passive movements of the upper limb, while participants either: i) focused attention exclusively on the task; or ii) simultaneously performed another task. Six healthy subjects participated in the study and results showed lower desynchronization during passive movements with another task simultaneously being carried out (compared to passive movements with exclusive attention on the task). In addition, it was proved the feasibility to distinguish between the two conditions.
JTD Keywords: Electrodes, Electroencephalography, Induction motors, Medical treatment, Robot sensing systems, Time frequency analysis, Biomechanics, Cognition, Electroencephalography, Medical robotics, Medical signal detection, Medical signal processing, Patient rehabilitation, Attention, Cognitive aspects, Desynchronization, Engagement, Motivation, Motor learning, Motor task, Motor-related EEG activity, Physical aspects, Robot-assisted passive movement detection, Robot-assisted rehabilitation therapies, Upper limb