Cloud-Connected Wireless Holter Monitor Machine with Neural Networks Based ECG Analysis for Remote Health Monitoring

This study describes the creation of a wireless, transportable Holter monitor to improve the accuracy of cardiac disease diagnosis. The main goal of this study is to develop a low-cost cardiac screening system suited explicitly for underprivileged areas, addressing the rising rates of cardiovascular death. The suggested system includes a wireless Electrocardiogram (ECG) module for real-time cardiac signal gathering using attached electrodes, with data transfer made possible by WiFi to a cloud server for archival and analysis. The system uses a neural network model for automated ECG classification, concentrating on the identification of cardiac anomalies. The diagnostic performance of cardiologist-level ECG analysis is surpassed by our upgraded deep neural network architecture, which underwent thorough evaluation and showed a stunning accuracy rate of more than 88\%. A quick, accurate, and reasonably priced option for cardiac screening is provided by this ground-breaking technology, which smoothly merges wireless data transfer with AI-assisted diagnostics. In addition to providing a thorough overview of the development process, this paper also highlights methods used to improve model accuracy, such as data preparation, class imbalance correction using oversampling, and model fine-tuning. The work shows the viability of a comprehensive remote cardiac screening system powered by AI and maximising the use of wearable and cloud computing resources. Such cutting-edge remote health monitoring technologies have great promise for improved health outcomes and early identification, especially in resource-constrained countries

Impact of Personality Trait of Agreeableness on Oral Parafunctional Habits

OBJECTIVES To find the impact of agreeable personality trait on oral parafunctional habits.METHODOLOGY A Cross-sectional descriptive study was conducted at the College of Dentistry, Sharif Medical and Dental College, Lahore, over 5 months, from July to November 2021. Data was collected using medical questionnaire and ten item personality inventory scale (TIPI). Kruskal Wallis test was to find the difference in the scores of agreeable personality trait across groups of oral parafunctional habits.RESULTSThere was a statistically significant difference in the agreeable personality trait across the parafunctional habits of tooth grinding (p=0.023) and biting on hard objects (p=0.013). A non-significant difference was seen in the personality trait across the habits of nail biting (p=0.495), tooth clenching (p=0.097) and habit of chewing gum (p=0.371). CONCLUSION The individuals who disagreed to having the habit of tooth grinding had the highest score for agreeableness and the least was seen in those who neither agreed nor disagreed to having the habit. The personality trait was the most prevalent in individuals who strongly agreed to having the habit of biting on hard objects and the least in those who agreed to having the habit