Literature DB >> 24654880

Could a new sensory pen assist in the early diagnosis of Parkinson's?

Richard W Walker1, Rutger Zietsma, William K Gray.   

Abstract

Neurodegeneration in Parkinson's disease (PD) affects both the fine motor control of the fingers and gross movement of the upper limb. Handwriting examinations are commonly performed in the analysis of tremor in PD and there is validity in subjective assessment in the clinic. However, there is clinical need for a more objective assessment instrument to assist in diagnosis. The Manus platform is a novel sensor system with automated mathematical methods, integrated with a digital pen, for differential diagnosis of PD that allows an objective assessment of handwriting. Our team are starting a clinical trial to assess the clinical usefulness of the system for differential diagnosis. The ability of the system to diagnose PD will be validated against the current best practice diagnosis of clinical opinion (or dopamine transporter imaging scan (DaTSCAN) imaging when an unequivocal diagnosis cannot be made). If the study proves clinically successful, the system may find application in clinics to aid in differentiating between impairments and be a low-cost alternative to DaTSCAN that can be operated with minimal training and is acceptable to patients.

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Year:  2014        PMID: 24654880     DOI: 10.1586/17434440.2014.900437

Source DB:  PubMed          Journal:  Expert Rev Med Devices        ISSN: 1743-4440            Impact factor:   3.166


  3 in total

Review 1.  Objective and quantitative assessment of motor function in Parkinson's disease-from the perspective of practical applications.

Authors:  Ke Yang; Wei-Xi Xiong; Feng-Tao Liu; Yi-Min Sun; Susan Luo; Zheng-Tong Ding; Jian-Jun Wu; Jian Wang
Journal:  Ann Transl Med       Date:  2016-03

2.  Amplitude Manipulation Evokes Upper Limb Freezing during Handwriting in Patients with Parkinson's Disease with Freezing of Gait.

Authors:  Elke Heremans; Evelien Nackaerts; Griet Vervoort; Sarah Vercruysse; Sanne Broeder; Carolien Strouwen; Stephan P Swinnen; Alice Nieuwboer
Journal:  PLoS One       Date:  2015-11-18       Impact factor: 3.240

3.  A Validation Study of Freezing of Gait (FoG) Detection and Machine-Learning-Based FoG Prediction Using Estimated Gait Characteristics with a Wearable Accelerometer.

Authors:  Satyabrata Aich; Pyari Mohan Pradhan; Jinse Park; Nitin Sethi; Vemula Sai Sri Vathsa; Hee-Cheol Kim
Journal:  Sensors (Basel)       Date:  2018-09-30       Impact factor: 3.576

  3 in total

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