Non-Invasive Sensors Integration for NCDs with AIoT Based Telemedicine System.
Chavis SrichanPobporn DanvirutaiNoppakun BoonsimAriya NamvongChayada SurawanitkunChanachai RitsongmuangApirat SiritaratiwatSirirat AnutrakulchaiPublished in: Sensors (Basel, Switzerland) (2024)
Thailand's hospitals face overcrowding, particularly with non-communicable disease (NCD) patients, due to a doctor shortage and an aging population. Most literature showed implementation merely on web or mobile application to teleconsult with physicians. Instead, in this work, we developed and implemented a telemedicine health kiosk system embedded with non-invasive biosensors and time-series predictors to improve NCD indicators over an eight-month period. Two cohorts were randomly selected: a control group with usual care and a telemedicine-using group. The telemedicine-using group showed significant improvements in average fasting blood glucose (148 to 130 mg/dL) and systolic blood pressure (152 to 138 mmHg). Data mining with the Apriori algorithm revealed correlations between diseases, occupations, and environmental factors, informing public health policies. Communication between kiosks and servers used LoRa, 5G, and IEEE802.11, which are selected based on the distance and signal availability. The results support telemedicine kiosks as effective for NCD management, significantly improving key NCD indicators, average blood glucose, and blood pressure.
Keyphrases
- blood glucose
- blood pressure
- public health
- healthcare
- glycemic control
- hypertensive patients
- primary care
- heart rate
- end stage renal disease
- ejection fraction
- quality improvement
- newly diagnosed
- systematic review
- machine learning
- heart failure
- chronic kidney disease
- palliative care
- mental health
- prognostic factors
- skeletal muscle
- risk assessment
- adipose tissue
- peritoneal dialysis
- big data
- patient reported outcomes
- metabolic syndrome
- chronic pain