Technology Of Health Related Data Sensing

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Technology in the area of health related data sensing is making some incredible advancements. Many people utilize wearables in their daily lives. For instance, Jawbone Fitness Trackers are gaining popularity. “This is an instrument that people wear on their wrists and the device connects via Bluetooth to the user’s smartphone. Depending on the model of Jawbone, the device has the ability to track a user’s activity levels, workouts, sleep, heart rate, etc. The device provides information and even suggestions to the user to encourage a healthier lifestyle” (“Jawbone”). Sensor driven technologies have also infiltrated sports. “The Reebok Checklight is a head covering equipped with sensors to detect when an athlete has taken a dangerous blow…show more content…
The contacts then communicate results to a sort of data receiver that is worn around the patient’s neck” (Lauren Gravitz). There are even ingestible sensors that monitor a person’s medication intake. “Not only does the ingestible sensor monitor medication intake, it also keeps track and communicates a person’s physical reaction to medications in the form of physical activity, sleep statistics, and blood pressure” (Hooman Hafezi 1).This innovation is a result of the fact that “between 30 percent and 50 percent of drugs prescribed to individuals are not actually consumed” (Hooman Hafezi 1). Incredible advances are inevitable in data sensing technology for health, but making use of the data is ultimately the biggest issue. Nearly all sensor technologies used in health collect some form of data. However, it is not simply enough to have the data. It can be analyzed and used in predictions, suggestions, and much more. This is where the big challenge lays and it is quite a multifaceted and complex issue. One concept that contributes to the overall challenge of health sensor data analytics is the fact that data can be rather segmented. One researcher writes that “many of these systems are already distributed by nature and that getting data into a centralized location for analysis not always an easy task, especially when considering cost of computing and patient privacy” (Daby Sow et al. 466). Sensor technologies and
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