title: Technologies for Assessment of Motor Disorders in Parkinson's Disease: A Review.
abstract: Parkinson's Disease (PD) is characterized as the commonest neurodegenerative illness that gradually degenerates the central nervous system. The goal of this review is to come out with a summary of the recent progress of numerous forms of sensors and systems that are related to diagnosis of PD in the past decades. The paper reviews the substantial researches on the application of technological tools (objective techniques) in the PD field applying different types of sensors proposed by previous researchers. In addition, this also includes the use of clinical tools (subjective techniques) for PD assessments, for instance, patient self-reports, patient diaries and the international gold standard reference scale, Unified Parkinson Disease Rating Scale (UPDRS). Comparative studies and critical descriptions of these approaches have been highlighted in this paper, giving an insight on the current state of the art. It is followed by explaining the merits of the multiple sensor fusion platform compared to single sensor platform for better monitoring progression of PD, and ends with thoughts about the future direction towards the need of multimodal sensor integration platform for the assessment of PD.
authors.affiliation: School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Campus Pauh Putra, 02600 Arau, Perlis, Malaysia. aliciaoung@gmail.com.
authors.forename: Qi Wei
authors.initials: QW
authors.lastname: Oung
authors.affiliation: School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Campus Pauh Putra, 02600 Arau, Perlis, Malaysia. hari@unimap.edu.my.
authors.forename: Hariharan
authors.initials: H
authors.lastname: Muthusamy
authors.affiliation: School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Campus Pauh Putra, 02600 Arau, Perlis, Malaysia. hoileong89@gmail.com.
authors.forename: Hoi Leong
authors.initials: HL
authors.lastname: Lee
authors.affiliation: School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Campus Pauh Putra, 02600 Arau, Perlis, Malaysia. shafriza@unimap.edu.my.
authors.forename: Shafriza Nisha
authors.initials: SN
authors.lastname: Basah
authors.affiliation: Universiti Kuala Lumpur Malaysian Spanish Institute, Kulim Hi-TechPark, 09000 Kulim, Kedah, Malaysia. sazali.yaacob@unikl.edu.my.
authors.forename: Sazali
authors.initials: S
authors.lastname: Yaacob
authors.affiliation: School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Campus Pauh Putra, 02600 Arau, Perlis, Malaysia. sarilleelee@gmail.com.
authors.forename: Mohamed
authors.initials: M
authors.lastname: Sarillee
authors.affiliation: School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Campus Pauh Putra, 02600 Arau, Perlis, Malaysia. mrlionryan@gmail.com.
authors.forename: Chia Hau
authors.initials: CH
authors.lastname: Lee
mesh_terms: D061725:Accelerometry; D020811:Biomedical Technology / Q000379:methods*; D006801:Humans; D008991:Monitoring, Physiologic; D000068079:Motor Disorders / Q000150:complications / Q000175:diagnosis* / Q000503:physiopathology*; D010300:Parkinson Disease / Q000150:complications / Q000175:diagnosis* / Q000503:physiopathology*
keywords: Parkinson Disease (PD); Unified Parkinson Disease Rating Scale (UPDRS); audio sensor; multimodal sensor; wearable sensor