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Affective Computing Applications and Challenges in Parkinson’s Disease: Diagnosis, Treatment, and Assistive Device Developments

Call for Papers

Parkinson’s disease (PD) is a neurodegenerative disorder which is mainly caused by the loss of neurotransmitters in basal ganglia and substantia nigra in brain. PD adversely affects the quality of life of nearly six million people all over the world. The primary symptoms of PD are tremor, muscular rigidity, bradykinesia (i.e., slowness of movement), and postural instability. These motor impairments are often accompanied by a wide range of nonmotor symptoms (e.g., depression, executive dysfunctions, sleep disturbances, and autonomic impairments); both motor and non-motor symptoms have a great impact on the quality of PD patient’s life. The PD symptoms appear gradually in patients, mostly over age of 60 (though also affecting younger patients) and this is often misinterpreted as a part of normal ageing. There is a growing evidence of cognitive and social impairments associated with this disease, particularly in emotion processing.

Emotion plays an important role in human to human communication and interaction. The ability to recognize the emotional states of people surrounding us is an important part of natural communication. Indeed, impairments in the ability to process emotions characterize several neuropsychiatric disorders and are likely to occur in PD and there is need for a method of quantifying emotions, which is currently performed through clinical ratings. The emerging technological developments in clinical and engineering research disciplines demonstrate different methods for assessing the cognitive functions of PD patients automatically. In this context, this special issue has the aim of addressing the key topics in affective computing using signal and image processing techniques for cognitive impairment analysis, diagnosis and rehabilitation systems, prediction, and long-term quality of life assessment of PD patients.

Potential topics include but are not limited to the following:

  • Facial emotion recognition and expression in PD
  • Intelligent signal and imaging methods in PD diagnosis
  • Machine learning approaches in PD diagnosis and treatment
  • Emotional impairment assessment in PD
  • Emotion and apathy in PD
  • Human machine interaction for PD patients
  • Assistive devices for PD
  • Internet of Things based development for PD
  • Novel methods for PD progression analysis
  • Speech recognition methods for PD diagnosis
  • Telemedicine systems in PD
  • Advances in sensors-based gait assessment of PD

Authors can submit their manuscripts through the Manuscript Tracking System at

Submission DeadlineFriday, 28 December 2018
Publication DateMay 2019

Papers are published upon acceptance, regardless of the Special Issue publication date.

Lead Guest Editor

  • M. Murugappan, Kuwait College of Science and Technology, Doha, Kuwait

Guest Editors