Wearable devices are digital diagnostic tools that have the potential to detect several diseases. They also play a role in providing personalized healthcare services. These wearables have the ability to monitor various psychological, physiological, and social variables. They also have their challenges. These challenges include safety, precision, energy consumption, computation and safety.
Since long, doctors have recommended wearing wearables to diagnose many conditions. Wearables are able to measure your physical activity and identify your emotional state. They can also be used to detect heart attacks in real time. Wearables require internet connectivity. These devices are not easily accessible in rural areas. Additionally, many in developing countries are unable to afford wearables because of their high cost.
The fitness activity monitors were the first form of wearable tech. These devices can be worn around the wrist and allow for continuous monitoring of many parameters. These data can be used for early diagnosis and to reduce deaths.
The latest innovations in wearables include smart tattoos with flexible electronic sensors. They can measure heart rate, muscle function, and sleep. Some researchers have even tested microchip implant, which are attached to the fingertip. These devices are based in radio-frequency identification and near field communication.
You can integrate wearables into your existing digital medical records. One example is a smart watch that can track a person's heart beat, oxygen saturation, and valence. Data gathered from wearables can be used to detect a variety of illnesses and disorders, including Alzheimer's disease, depression, and Parkinson's disease. Wearables can monitor heart attacks in real time and detect dyskinesia in PD sufferers.
Wearables have become increasingly dependent on machine learning algorithms. Wearables can provide highly personalized information about the body through machine-learning methods (ML). Machine-learning can be used to identify emotional and psychological conditions. Wearables with ML can help clinicians better understand patient-reported behavior and create more effective treatments. Wearables can also be used to assist patients in making treatment decisions.
Wearable smart devices can be used to treat social anxiety and sleep disorders. Ko et. Ko et al. compared ECG data to heart rate data obtained from wearable devices and found the former was more accurate. Furthermore, a clinical trial with over 60 adults showed that self-monitoring using a wearable led to an earlier diagnosis.
Nelson et.al. also found similar results. Nelson et. al. also compared Fitbit data and Apple Watch accuracy to ECG data. Results showed that the accuracy of the Apple Watch was better than the Fitbit, which failed to meet the accuracy guidelines. Despite this, this study suggests that ML algorithms could be used to improve the accuracy of wearable data.
Wearables are now able to diagnose many ailments thanks to the development of ML algorithms. They can be used for diagnosing specific diseases. This can lead to better treatments.