Parkinson’s Disease Symptom Detection using Hybrid Feature Extraction and Classification Model

Abdullah, Muhammad Irsyad; Hao, Shuai; Abdullah, Ibrahim; Faizah, Safira

doi:10.1109/icsgrc57744.2023.10215477

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…>0.05, it meant that the values on the x, y, and z axis had no simultaneous effect on the frequency value. Subsequently, during the ANOVA test, the degree of freedom (df) is calculated as shown in (1):…”

Section: Anova Testmentioning

confidence: 99%

“…It impacts different body areas and manifests through motor signs like tremors, akinesia, rigidity, bradikinesia, postural unpredictability and challenges in walking, and rigidity in posture. Furthermore, PD can lead to non-motor symptoms like cognitive deficiencies such as memory loss and difficulties in thinking [1]- [6]. Most individuals receive a PD diagnosis in their 70s, although 15% of cases occur in those under 50 years old.…”

Section: Introductionmentioning

confidence: 99%

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A rest tremor detection system based on internet of thing technology

Faizah,

Nugraha,

N. Abdulrazaq

et al. 2024

IJEECS

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<span>This article outlines the creation of a health detection system designed to identify rest tremors in Parkinson's disease (PD). The system leverages internet of things (IoT) technology to measure frequencies derived from human activities, excluding other symptoms such as heartbeat and voice recording. The core components include the Arduino Nano microcontroller and the Node ESP MCU 8266 V3 for data processing. The system employs an accelerometer sensor positioned at the body's center axis to gauge the frequency of motor symptoms associated with resting tremors, particularly when the hands are at rest in the lap. The findings indicate that 9 samples displayed symptoms of rest tremor. The recorded p-value, standing at 0.884, signifies a robust correlation between the two variables at a significant threshold of 0.01 or 1%.</span>

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Section: Anova Testmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%