Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance

One in twenty-five patients admitted to a hospital will suffer from a hospital acquired infection. If we can intelligently track healthcare staff, patients, and visitors, we can better understand the sources of such infections. We envision a smart hospital capable of increasing operational efficiency and improving patient care with less spending. In this paper, we propose a non-intrusive vision-based system for tracking people's activity in hospitals. We evaluate our method for the problem of measuring hand hygiene compliance. Empirically, our method outperforms existing solutions such as proximity-based techniques and covert in-person observational studies. We present intuitive, qualitative results that analyze human movement patterns and conduct spatial analytics which convey our method's interpretability. This work is a step towards a computer-vision based smart hospital and demonstrates promising results for reducing hospital acquired infections.Comment: Machine Learning for Healthcare Conference (MLHC

Healthcare Event and Activity Logging.

The health of patients in the intensive care unit (ICU) can change frequently and inexplicably. Crucial events and activities responsible for these changes often go unnoticed. This paper introduces healthcare event and action logging (HEAL) which automatically and unobtrusively monitors and reports on events and activities that occur in a medical ICU room. HEAL uses a multimodal distributed camera network to monitor and identify ICU activities and estimate sanitation-event qualifiers. At the core is a novel approach to infer person roles based on semantic interactions, a critical requirement in many healthcare settings where individuals' identities must not be identified. The proposed approach for activity representation identifies contextual aspects basis and estimates aspect weights for proper action representation and reconstruction. The flexibility of the proposed algorithms enables the identification of people roles by associating them with inferred interactions and detected activities. A fully working prototype system is developed, tested in a mock ICU room and then deployed in two ICU rooms at a community hospital, thus offering unique capabilities for data gathering and analytics. The proposed method achieves a role identification accuracy of 84% and a backtracking role identification of 79% for obscured roles using interaction and appearance features on real ICU data. Detailed experimental results are provided in the context of four event-sanitation qualifiers: clean, transmission, contamination, and unclean

Optical based noninvasive glucose monitoring sensor prototype

Diabetes mellitus claims millions of lives every year. It affects the body in various ways by leading to many serious illnesses and premature mortality. Heart and kidney diseases, which are caused by diabetes, are increasing at an alarming rate. In this paper, we report a study of a noninvasive measurement technique to determine the glucose levels in the human body. Current existing methods to quantify the glucose level in the blood are predominantly invasive that involve taking the blood samples using finger pricking. In this paper, we report a spectroscopy-based noninvasive glucose monitoring system to measure glucose concentration. Near-infrared transmission spectroscopy is used and in vitro experiments are conducted, as well as in vivo. Our experimental study confirms a correlation between the sensor output voltage and glucose concentration levels. We report a low-cost prototype of spectroscopy-based noninvasive glucose monitoring system that demonstrates promising results in vitro and establishes a relationship between the optical signals and the changing levels of blood–glucose concentration

Mobihealth: mobile health services based on body area networks

In this chapter we describe the concept of MobiHealth and the approach developed during the MobiHealth project (MobiHealth, 2002). The concept was to bring together the technologies of Body Area Networks (BANs), wireless broadband communications and wearable medical devices to provide mobile healthcare services for patients and health professionals. These technologies enable remote patient care services such as management of chronic conditions and detection of health emergencies. Because the patient is free to move anywhere whilst wearing the MobiHealth BAN, patient mobility is maximised. The vision is that patients can enjoy enhanced freedom and quality of life through avoidance or reduction of hospital stays. For the health services it means that pressure on overstretched hospital services can be alleviated

GUI system for Elders/Patients in Intensive Care

In the old age, few people need special care if they are suffering from specific diseases as they can get stroke while they are in normal life routine. Also patients of any age, who are not able to walk, need to be taken care of personally but for this, either they have to be in hospital or someone like nurse should be with them for better care. This is costly in terms of money and man power. A person is needed for 24x7 care of these people. To help in this aspect we purposes a vision based system which will take input from the patient and will provide information to the specified person, who is currently may not in the patient room. This will reduce the need of man power, also a continuous monitoring would not be needed. The system is using MS Kinect for gesture detection for better accuracy and this system can be installed at home or hospital easily. The system provides GUI for simple usage and gives visual and audio feedback to user. This system work on natural hand interaction and need no training before using and also no need to wear any glove or color strip.Comment: In proceedings of the 4th IEEE International Conference on International Technology Management Conference, Chicago, IL USA, 12-15 June, 201

A comprehensive survey of wireless body area networks on PHY, MAC, and network layers solutions

Recent advances in microelectronics and integrated circuits, system-on-chip design, wireless communication and intelligent low-power sensors have allowed the realization of a Wireless Body Area Network (WBAN). A WBAN is a collection of low-power, miniaturized, invasive/non-invasive lightweight wireless sensor nodes that monitor the human body functions and the surrounding environment. In addition, it supports a number of innovative and interesting applications such as ubiquitous healthcare, entertainment, interactive gaming, and military applications. In this paper, the fundamental mechanisms of WBAN including architecture and topology, wireless implant communication, low-power Medium Access Control (MAC) and routing protocols are reviewed. A comprehensive study of the proposed technologies for WBAN at Physical (PHY), MAC, and Network layers is presented and many useful solutions are discussed for each layer. Finally, numerous WBAN applications are highlighted

Development of Wearable Systems for Ubiquitous Healthcare Service Provisioning

This paper reports on the development of a wearable system using wireless biomedical sensors for ubiquitous healthcare service provisioning. The prototype system is developed to address current healthcare challenges such as increasing cost of services, inability to access diverse services, low quality services and increasing population of elderly as experienced globally. The biomedical sensors proactively collect physiological data of remote patients to recommend diagnostic services. The prototype system is designed to monitor oxygen saturation level (SpO2), Heart Rate (HR), activity and location of the elderly. Physiological data collected are uploaded to a Health Server (HS) via GPRS/Internet for analysis.Comment: 6 pages, 3 figures, APCBEE Procedia 7, 2013. arXiv admin note: substantial text overlap with arXiv:1309.154