Wearable health technology has transformed health monitoring and management by allowing continuous tracking of vital signs, physical activity and other health parameters. However, while traditional wearables depend on simple algorithms and user input, thus limiting their capacity to provide wide-ranging health insights, integrating artificial intelligence (AI) into wearable health devices promises to elevate personalised healthcare by facilitating real-time data analysis and early detection of health problems.

These body-worn devices have evolved from simple fitness trackers into critical instruments for comprehensive wellness and chronic disease management. With the rising occurrence of chronic ailments like diabetes, cardiac conditions and cancer, together with an ageing population, the need for remote health monitoring solutions has seen an exponential adoption rate.

These innovative devices are capable of collecting, analysing and transmitting real-time health data, enabling healthcare providers to make informed decisions and improve patient care. These solutions also help the user in better self-management of sleep, stress and daily activities.

Role of AI in wearable health tech

AI is revolutionizing the wearable health tech industry by harnessing data to deliver valuable insights and personalized health recommendations through predictive analytics. The advantages of this technology are immense. These are some:

# Data analysis and insights: Wearable devices gather enormous quantities of data every day. AI algorithms help analyse this data to detect patterns and provide actionable insights. For example, AI can detect irregular heartbeats from ECG data, warning users to potential heart issues before they aggravate.

# Customized health recommendations: With AI, wearable health tech can offer personalised health advice based on individual behaviours and predilections. By analysing activity levels, dietary habits and vital signs, these gadgets can recommend tailored fitness regimens or dietary adjustments to help users achieve their health objectives.

# Predictive analytics: By analysing historical data, AI can predict potential health risks. For instance, through machine learning (ML) models, a wearable device can predict the probability of a user developing conditions like diabetes or hypertension, based on their activity patterns and physiological data.

# Elevated user engagement: AI-generated features can boost user involvement by providing interactive and motivating experiences. Personalised challenges, reminders and feedback inspire users to keep up their health routines, thus making it easier to stay steadfast to their wellness targets.

# Integration with healthcare systems: Wearable devices equipped with AI can easily integrate with healthcare systems, enabling doctors to access real-time patient data. This integration supports remote monitoring and timely interventions, improving patient outcomes and minimising hospital visits.

# Medicine Dispensing Alert : To alert seniors to take medicines at appropriate time and interval have also been developed.

Types of healthcare-linked wearables

· Fitness trackers monitor physical activity data like steps taken, calories burned, distance traversed, and even heart rate. They often sync with smartphone apps, to provide understandings of fitness levels and goals.

· Heart rate monitors available as chest straps, wristbands or even embedded in smart clothing, constantly monitor heart rate during exercise and routine activities, offering insights into cardiovascular health.

· Wearable BP monitors measure blood pressure throughout the day, providing data to track and manage hypertension. Some devices can even detect irregular heart rhythms.

· Sleep trackers are wearables that monitor sleep patterns, including duration, stages of sleep (light, deep, REM), and interruptions. These trackers provide insights into sleep quality and can offer advice for improving sleep hygiene.

· Smart clothing comprises textiles embedded with sensors to monitor biometric data like heart rate, respiration rate, muscle activity and body temperature. Such clothing provides constant monitoring without the need for separate devices.

· Posture correctors are devices that track posture and offer feedback to users to improve spinal alignment and reduce musculoskeletal strain.

· Fall detection devices are wearables equipped with sensors to detect falls and send alerts to caregivers or emergency services.

· Wearable sensors for health monitoring can be classified into three main types – physical sensors to measure physical and physiological signals, chemical sensors and biosensors which detect chemical signals.

· Multifunctional AI hearing aids assist hearing-impaired people in “feeling” the environment and can use natural language processing.

These devices are revolutionizing clinical and healthcare services by facilitating a shift from centralized diagnostics to more personalized home care. With breakthroughs in wireless technology and AI, these smart wearable sensors and technologies can be customized to suit individual requirements and are easily accessible to patients.