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Background: Current Huntington's disease (HD) measures are limited to subjective, episodic assessments conducted in clinic. Smartphones can enable the collection of objective, real-world data but their use has not been extensively evaluated in HD.
Objective: Develop and evaluate a smartphone application to assess feasibility of use and key features of HD in clinic and at home.
Methods: We developed GEORGE®, an Android smartphone application for HD which assesses voice, chorea, balance, gait, and finger tapping speed. We then conducted an observational pilot study of individuals with manifest HD, prodromal HD, and without a movement disorder. In clinic, participants performed standard clinical assessments and a battery of active tasks in GEORGE. At home, participants were instructed to complete the activities thrice daily for one month. Sensor data were used to measure chorea, tap rate, and step count. Audio data was not analyzed.
Results: Twenty-three participants (8 manifest HD, 5 prodromal HD, 10 controls) enrolled, and all but one completed the study. On average, participants used the application 2.1 times daily. We observed a significant difference in chorea score (HD: 19.5; prodromal HD: 4.5, p = 0.007; controls: 4.3, p = 0.001) and tap rate (HD: 2.5 taps/s; prodromal HD: 8.9 taps/s, p = 0.001; controls: 8.1 taps/s, p = 0.001) between individuals with and without manifest HD. Tap rate correlated strongly with the traditional UHDRS finger tapping score (left hand: r = -0.82, p = 0.022; right hand: r = -0.79, p = 0.03).
Conclusion: GEORGE is an acceptable and effective tool to differentiate individuals with and without manifest HD and measure key disease features. Refinement of the application's interface and activities will improve its usability and sensitivity and, ideally, make it useful for clinical care and research.
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http://dx.doi.org/10.3233/JHD-200452 | DOI Listing |
Light Sci Appl
September 2025
State Key Laboratory of Flexible Electronics, Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications (NUPT), Nanjing, 210023, China.
As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components.
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Pulmonary and Critical Care Medicine, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China.
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Department of Psychiatry, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, Republic of Korea.
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View Article and Find Full Text PDFTalanta
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Karamanoglu Mehmetbey University, Kamil Ozdag Science Faculty, Department of Chemistry, Karaman, 70100, Turkey.
Biogenic amines (BAs) are organic nitrogen compounds formed through microbial decarboxylation of amino acids during food spoilage and biological metabolism. Therefore, the development of rapid, selective, and cost-effective detection strategies for BAs is significant for ensuring food safety and quality. In this study, a new dicyanoisophorone-based fluorescent probe (IPC) was developed, capable of fluorescence detection of aliphatic primary amines (e.
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