D2.1 Requirements and Specification - CORBYS

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D2.1 Requirements and Specification In the CORBYS context, perception sensing will be used for the following purposes: � User safety � Physical effort � Characterisation of gait parameters � Psycho-physiological states � User intention With few exceptions, extraction of meaningful parameters in these cases requires a multi sensor approach and can not be drawn based on single sensors alone. Compared to other gait rehabilitation research, CORBYS is in a quite unique position in being able to combine physiological sensors with EEG information. Below, we outline what type of sensor information might be of interest within CORBYS to assess the gait rehabilitation session and to provide sensory input to the CORBYS cognitive robotic control algorithms. Ensuring user safety: For user safety it is important to ensure that the position of extremities and joint angles are reasonable. For CORBYS gait rehabilitation system it will then be monitoring: � Mechanical switches � Consistency between measured body positions and robot actuator position Assessing physical effort: Physical effort will tell the therapist about the work load of the patient, and may also be input to the cognitive control system. For assessing physical effort the following parameters are judged most valuable: � Heart rate � Respiratory rate � Activity information � Force sensors � Temperature � Sweat/humidity � EMG � EEG � Input from robot actuators Characterisation of gait Characterisation of movements is also of interest. Characterisation on biomechanics is already a big field and applications range from gait rehabilitation [Avor and. Sarkodie-Gyan, 2009 ] to technical analysis within the field of sport [Myklebust et al, 2011]. Within the CORBYS settings we consider combination of these parameters most promising in the characterisation of gait: � Inertial measurement units information � Force sensors � Angular/torque measurements 110
D2.1 Requirements and Specification � EMG � Input from robot actuators Identifying psycho-physiological states Extensive research effort has been put into the field of physiological computing, which is the term used to describe any computing system that uses real-time physiological data as an input stream to control the user interface 15 . The review article Fundamentals of Physiological Computing [Fairclough, 2009] summarises some of the challenges and the complexity in developing a physiological computing system that employs a real-time measure of psycho-physiology to communicate the physiological state of the user to an adaptive system. As summarised in this article the physiological state of the user has been represented e.g. as one-dimensional continuum of frustration, anxiety, task engagement, mental workload, or two-dimensional space of activation and valence. The detection of negative emotions may be particularly relevant for computing applications designed to aid learning [Picard et al, 2004]. Heart rate is one of the most common parameters used to detect stress of the affective state [Rani et al, 2002], together with EMG, EDR and facial expression [Rani et al, 2004] [Kulic and Croft, 2007]. Within the CORBYS settings we consider combination of these parameters most promising in order to identify psycho-physiological states. � Heart rate � EMG � EDR � EEG Identifying intention CORBYS has a vision of being able to identify and help assist the user carry out his/her intentions. This is however very challenging since there are no or few clear manifestations of intention in physiological measurements, and the sensor information is blurred by all other factors impacting the measurements. It is probably therefore wise to limit the ambitions to being able to identify whether the patient wants to carry on making a cyclic movement such as walking or whether the patient wants to stop. For this purpose the following CORBYS components can be considered: 1. EEG 2. EDR 3. EMG 4. Heart rate 10.4 Summary on technology gaps and priorities for development in CORBYS The SOA analysis shows that many sensor concepts are developed and relatively mature. It is therefore to a limited extent necessary to develop entirely new sensor concepts. The best path for innovation in the field is through a clever combination of existing sensor concepts. The combination can either be through a physical integration of different sensor concepts, or it can be the combination of sensor data in order to come up with 15 http://www.physiologicalcomputing.net/ 111
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CORBYS Cognitive Control Framework
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D2.1 Requirements and Specification
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D2.1 Requirements and Specification - CORBYS

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