A Survey of Sensors in Healthcare Workflow Monitoring

Abstract

Activities of a clinical staff in healthcare environments must regularly be adapted to new treatment methods, medications, and technologies. This constant evolution requires the monitoring of the workflow, or the sequence of actions from actors involved in a procedure, to ensure quality of medical services. In this context, recent advances in sensing technologies, including Real-time Location Systems and Computer Vision, enable high-precision tracking of actors and equipment. The current state-of-the-art about healthcare workflow monitoring typically focuses on a single technology and does not discuss its integration with others. Such an integration can lead to better solutions to evaluate medical workflows. This study aims to fill the gap regarding the analysis of monitoring technologies with a systematic literature review about sensors for capturing the workflow of healthcare environments. Its main scientific contribution is to identify both current technologies used to track activities in a clinical environment and gaps on their combination to achieve better results. It also proposes a taxonomy to classify work regarding sensing technologies and methods. The literature review does not present proposals that combine data obtained from Real-time Location Systems and Computer Vision sensors. Further analysis shows that a multimodal analysis is more flexible and could yield better results.

A review on video-based active and assisted living technologies for automated lifelogging

“…context awareness based on wearable or ambient sensors (contact, radio) can be limited (Antunes et al, 2018). Other fields of AAL such as health monitoring and diagnostics (tele-health) rely mostly on other sensors, as these are 270 considered to be less error-prone and/or have undergone approval from regulatory medical agencies (Faust et al, 2018).…”

“…As a related field, AAL does not scape this trend either. Finally, some of the reviews explored are done from a systematic review perspective (Antunes et al, 2018;Bygholm & Kanstrup, 2015;Calvaresi et al, 2017). Following this methodology, one starts by setting some main research 310 questions.…”

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“…We are using the computing node with such configuration since in future works we are planning to employ Computer Vision strategies and perform experiments that consider the extraction of depth and color images from camera devices to estimate human poses. We consider this kind of experiments due to these strategies be present in healthcare environments [68]. We deployed the remaining QualiCare components, including the QualiCare Manager, in an additional server node.…”

Knowledge-Based Decision Support in Healthcare via Near Field Communication

“…In healthcare, different types of practitioners interact with patients in various activities, which are typically coordinated in complex workflows, possibly involving several territorial Point-of-Care (POC) facilities [ 5 , 10 ]. Capabilities of NFC technology [ 9 ] can be leveraged to improve healthcare operations.…”