Clustering of Emotional States under Different Task Difficulty Levels for the Robot-assisted Rehabilitation system-RehabRoby

Robot-assisted rehabilitation systems have shown to be helpful in neuromotor rehabilitation because it is possible to deliver interactive and repeatable sensorimotor exercise and monitor the actual performance continuously. Note that it is also essential to distinguish if subject finds the rehabilitation task difficult or easy, since the difficulty level of a task can yield different emotional state, such as excited, bored, over-stressed, etc., at each subject. It is important to adjust the difficulty level of the task to encourage the non-motivated subjects during the therapy. The physiological measurements, which can be obtained from the biofeedback sensors, can be used to estimate the subject's emotional state during the execution of the rehabilitation task. Machine learning methods can be used to classify the emotional state using the features of the biofeedback sensory data. This is explored in this chapter.

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Classification of the Emotional State of a Subject Using Machine Learning Algorithms for RehabRoby

Barkana

¹

,

Maşazade

²

Artificial Intelligence

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Robot-assisted rehabilitation systems have shown to be helpful in neuromotor rehabilitation because it is possible to deliver interactive and repeatable sensorimotor exercise and monitor the actual performance continuously. Note that it is also essential to distinguish if subject finds the rehabilitation task difficult or easy, since the difficulty level of a task can yield different emotional state, such as excited, bored, over-stressed, etc., at each subject. It is important to adjust the difficulty level of the task to encourage the non-motivated subjects during the therapy. The physiological measurements, which can be obtained from the biofeedback sensors, can be used to estimate the subject's emotional state during the execution of the rehabilitation task. Machine learning methods can be used to classify the emotional state using the features of the biofeedback sensory data. This is explored in this chapter.

show abstract

Clustering of Emotional States under Different Task Difficulty Levels for the Robot-assisted Rehabilitation system-RehabRoby

Cited by 4 publications

References 28 publications

Emotional state and cognitive load analysis using features from BVP and SC sensors

Emotional state and cognitive load analysis using features from BVP and SC sensors

Classification of the Emotional State of a Subject Using Machine Learning Algorithms for RehabRoby

Classification of the Emotional State of a Subject Using Machine Learning Algorithms for RehabRoby

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