研究目的
To examine the available literature on smartphone applications for assessment of Parkinson’s disease motor and nonmotor symptoms and signs.
研究成果
There are important advances on smartphone-based tools for objective, relevant, accurate information on motor and nonmotor aspects of PD. Research is still needed to overcome various limitations of nonelectronic and smartphone-based tools for assessments and monitoring of PD symptoms and signs and to build smartphone applications that may improve the quality of life of PD patients.
研究不足
The quality of evidence related to the use of smartphone-based applications for PD diagnosis or monitoring was not high, indicating the need for more research for the validation of the new technologies, methods, and their performances across various PD subtypes and degrees of disease severity, in clinical laboratory settings, in home, or community settings.
1：Experimental Design and Method Selection:
A systematic review of papers related to smartphone applications for Parkinson’s disease symptoms and signs assessment and monitoring was carried out. Papers published from 2013 to 2017 listed in two electronic databases—Medline via PubMed and IEEE/IET Electronic Library, IEEE Xplore—were searched by title and abstract to identify the works related to smartphone use for diagnosis and monitoring patients with Parkinson’s disease.
2：Sample Selection and Data Sources:
The search was made using the terms: "smartphone AND Parkinson’s disease," considering 5 years (2013–2017). To be eligible for inclusion, papers were required to be available in English; include patient(s) with Parkinson’s disease; include assessment of Parkinson’s disease symptoms, signs, and treatment outcomes by using a smartphone.
3：7). To be eligible for inclusion, papers were required to be available in English; include patient(s) with Parkinson’s disease; include assessment of Parkinson’s disease symptoms, signs, and treatment outcomes by using a smartphone. List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: Smartphones with various sensors (inertial measurement units, capacitive, force/pressure, acoustic sensors) were used.
4：Experimental Procedures and Operational Workflow:
Each record identified through database searching was screened based on their title and abstract and a decision was made based on the criteria above on the suitability of inclusion of the papers in our analysis. The analyzed papers were categorized by technology and the symptoms or treatment outcome that was evaluated.
5：Data Analysis Methods:
The analysis of full-text articles has taken into account the validity, reliability, and sensitivity to change the technique used in the measurements as well as the GRADE—Grading of Recommendations Assessment, Development and Evaluation guideline.
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