Healthcare Advancements Through AI-driven Smartwatches

Healthcare Advancements Through AI-driven Smartwatches

Smartwatch is a mini wearable computer with a touch screen facility. It helps in connecting with the smartphone apps for tracking and managing the telemetry such as long-time biomonitoring. Initially, smartwatches had basic features such as a calculator, digital time telling, translations, and game-playing. Nowadays it is equivalent to smartphones which include features such as built-in FM, call-in features and many more.

Smartwatches are one of the most common gadgets around us. It is forecasted that the global sales of smartwatches would increase to about 115 million by 2022.

Some of the biomonitoring features of smartwatches are:

  • The tracking number of steps:  Mechanical pedometers will measure steps through the motion of a mechanical pendulum or metal ball. A similar system is used in digital pedometers, but it’s integrated as part of a wider circuit.
  • Weekly MVPA mins and sedentary time: This is mainly measured using the accelerometer. 
  • Heart rate: This is calculated using the PPG technology. It is a low-infrared ray technology. It travels through the tissues which are absorbed by bones, venous and arteries, skin pigments. The voltage signal from PPG is proportional to the quantity of blood flow in blood vessels. This helps in measuring the heart rate.
  • Calories burned: The method used to measure the calories burnt varies across different companies. Few use BMR, activity rate and manually entered activity.  
  • Sleep patterns: It is measured using actigraphy.

The smartwatches mainly use 

  • Optical sensor 
  • Contact sensor 
  • Altimeter 
  • GPS 
  • Accelerometer 
  • Gyroscope 

The data provided by these sensors and other built-in features play a vital role in assessing the patient’s health. The data when coupled with artificial intelligence analysis can prove to be a breakthrough in the healthcare industry.

Some of the major inventions where AI-driven smartwatches have helped in gaining a leap in the healthcare industry are:

Monitoring blood pressure: This is mainly monitored by calculating the pulse transit time using the combination of an Electrocardiogram sensor and an optical heart rate sensor. Pulse transit time is the time taken by a pulse wave to travel between two arterial sites. The speed at which this arterial pressure wave travels is directly proportional to blood pressure.

Respiratory issues: This can be detected by tracking the blood oxygen saturation levels using the blood oxygen saturation sensors. Blood oxygen saturation level indicates the oxygen level present in the blood that flows through the arteries. Few of the companies have come up with the combination of this sensor to track respiratory issues.

Detection of atrial fibrillation: The smartwatches from Fitbit, Apple and Samsung have incorporated Electrocardiogram (ECG) function to detect the electric signals by the heart.

Detection of sleep Apnea: Most company smartwatches use the facility to track sleep time, few combine this with the tracking of SPO2 levels. This can help in throwing more light on the early detection of Sleep Apnea. 


The upcoming major inventions using AI-driven smartwatches are

Monitoring Blood Glucose level:  Samsung and Apple watches are on the verge of including glucose sensors in the smartwatch. This can prove to be a breakthrough in monitoring continuous blood sugar levels. As of now the blood sugar level is monitored mainly using the invasion technique, which is cumbersome, painful, and expensive. The non-invasive method would prove a boon for patients who would check the blood glucose level regularly.

Detection of COVID: Attempts by many companies have been made to detect COVID using smartwatches. This would use the combination of altering heart rate, sleep rate, skin temperature variation (temperature sensors).

Hence with more collaboration of health care data with the artificial intelligence analysis, more advancements can be brought in the healthcare field. The existing methods would become less invasive and less cumbersome. It would also help in diagnosing, treating or preventing the diseases at early stages which would be a boon to the patients. This would also lead to a better and longer lifespan.

I have experience in the healthcare industry for more than ten years. I am a passionate blogger who is interested in writing on healthcare, technology advancements.
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I have experience in the healthcare industry for more than ten years. I am a passionate blogger who is interested in writing on healthcare, technology advancements.
follow me
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Written by Prasidha Ramnathan
I have experience in the healthcare industry for more than ten years. I am a passionate blogger who is interested in writing on healthcare, technology advancements.
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