Generic sensor framework enabling personalized healthcare

Abstract

Data and sensor fusion can enable clinical healthcare systems to improve conditions of a patient. However, hospitals are not the only application field of connected medical devices. Domestic monitoring gets more important day by day and applies Internet of Things with mobile sensors, like wearables. Through data processing data is transferred to smart data and personalized recommendations are improvable, if sensors can be chosen individually. Therefore, we developed a generic medical sensor framework which is able to merge any needed sensor and collect data to improve personalized health of an individual. To evaluate our framework and to prove the added value of sensor fusion we present a sensor-based stress detection game.

Healthcare in Asymmetrically Smart Future Environments: Applications, Challenges and Open Problems

“…The percentages add up to more than 100% since most studies discuss more than one sensor type, leading to overlaps in the category analysis. The use of sensors and actuators was classified according to the criteria defined by Beckman et al [56]. They describe three broad categories: These classifications are primarily differentiated by how closely the IoMT devices are fitted to the patient's body or distributed within the space the patient is occupying.…”

“…Nearables are devices that occupy the same physical space as the rehabilitating patient [56]. Unlike smart wearables, such as fitness trackers or blood pressure monitors, they are not attached to the patient's body [12,15].…”

“…Sensor Fusion: Beckmann et al [56] explain that combining data from multiple different types of sensors, referred to as sensor fusion, leads to more personalized and accurate patient interventions. It also increases the number of possible sensors that could be chosen to address a patient's needs.…”

“…This protocol describes how low-powered devices worn by the patient communicate through base-station gateways in the home. Beckmann et al [56] further explain the role of the OSAS architecture in standardizing the integration of incompatible devices from multiple vendors. The studies describe how network gateways can be augmented with the use of mobile smart devices [54,68,75], referencing generic networking standards such as IEEE 802.11-2012 [76].…”

The Effect of Real-Time Feedback on Indoor Environmental Quality

“…Figure 2 displays the technical infrastructure. Technically, it uses the Java Data Collecting Framework (JDCF) from Beckmann et al [42] to collect and process data. Following their suggestion, we describe the data flow along the dimensions Person & Environment, Connection, Processing, Usage, and Persistence.…”