Eric Campo

Bio: Eric Campo is an academic researcher from Hoffmann-La Roche. The author has contributed to research in topics: Wireless sensor network & Wireless network. The author has an hindex of 7, co-authored 26 publications receiving 208 citations. Previous affiliations of Eric Campo include University of Toulouse & Électricité de France.

Activity monitoring system for elderly in a context of smart home

Abstract: The Homecare project which is part of a research project funded by the French National Research Agency (ANR), aims to define and experiment a new multi-sensor monitoring system for the elderly with cognitive disabilities in a care unit. The main objective of this project is to follow activities of patients in their living environment. The system consists in a motion sensors network deployed on different areas of the care unit and in an electronic patch worn by the subject to identify him and detect falls. In order to locate tagged subjects inside the care unit we use a network of anchor points. From these positions and movement data, an analysis algorithm detects an abnormal situation and alerts the nursing staff in real time. A web application allows the medical staff to access movements and alarms. The complete monitoring system is functional for several months and monitor continuously two patients 24/24. The first results are encouraging. Seven out of eight falls were detected with one false alarm every week. Finally, activities monitoring allowed medical staff to tailor a treatment for one subject followed. In this paper, we present the system architecture, the technologies used, and some results.

Design and evaluation of a device worn for fall detection and localization: Application for the continuous monitoring of risks incurred by dependents in an Alzheimer’s care unit

Abstract: The Homecare project, which is part of a research project funded by the French National Research Agency (ANR), aims to define a new multi-sensor monitoring system for the elderly with cognitive disabilities in a care unit. Two subjects were recruited to participate to experimental trials. The main objective of this project is to design and test a complete monitoring system at a real site. It is a new clinical and technical approach which is complex to implement: Homecare is intended to propose a possible technical solution, demonstrate its feasibility and illustrate its use working at a protected site. The system consists of a motion sensor network deployed on the ceiling to monitor motion and an electronic patch worn by the subjects to identify them and detect falls. In order to locate tagged subjects inside the care unit, a network of anchor points is used. From these positions and movement data, an analysis algorithm detects an abnormal situation and alerts the nursing staff in real time. A Web application allows the medical staff to access movements and alarms. The complete monitoring system has been functioning for several months and continuously monitors two patients around the clock. In this paper, we present the implementation of the system, the method of localization inside the care unit, and the characterization of the fall detector, and we show certain results relating to activity data.

Validation of a remote monitoring system for the elderly: Application to mobility measurements

Abstract: The aim of this paper is to introduce a smart tool for the assessment of the mobility of patient with motor disorders and to evaluate its performance through some initial experiments. These experiments are based on a system which is composed of sensors connected to a Personal Computer (PC) using data acquisition cards and a communication network. The PC includes a data acquisition and processing software. This system has been installed in a patient's housing (a bedroom and a washroom) in a long-stay setting. Pre-established travel and activity (going to bed, getting up, visiting the washroom…) patterns of patient in the housing including their duration have been defined by physicians for the experiments. A volunteer participated in the experiments and the results of his mobility obtained by the data processing software were compared with his real mobility. An agreement was found between the proposed assessment system and the experiments, thereby validating functioning of the whole system. Then, the system has been used to monitor a patient over a period of 39 nights. Again there is a good agreement between the characteristics derived from the system and the findings of the caring staff in charge of the patient's routine night monitoring. Data collected during 24 consecutive hours have been used to identify and characterise the patient's whole day mobility. This study paves the way for a new assessment system of the mobility of patient thus allowing the follow up of patients suffering from dementia and to study their significant mobility changes over time by introducing an indicator of mobility which can be used to assess their motor behavioural disorders.

Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review

Abstract: Background: Sleep is essential for human health. Considerable effort has been put into academic and industrial research and in the development of wireless body area networks for sleep monitoring in terms of nonintrusiveness, portability, and autonomy. With the help of rapid advances in smart sensing and communication technologies, various sleep monitoring systems (hereafter, sleep monitoring systems) have been developed with advantages such as being low cost, accessible, discreet, contactless, unmanned, and suitable for long-term monitoring. Objective: This paper aims to review current research in sleep monitoring to serve as a reference for researchers and to provide insights for future work. Specific selection criteria were chosen to include articles in which sleep monitoring systems or devices are covered. Methods: This review investigates the use of various common sensors in the hardware implementation of current sleep monitoring systems as well as the types of parameters collected, their position in the body, the possible description of sleep phases, and the advantages and drawbacks. In addition, the data processing algorithms and software used in different studies on sleep monitoring systems and their results are presented. This review was not only limited to the study of laboratory research but also investigated the various popular commercial products available for sleep monitoring, presenting their characteristics, advantages, and disadvantages. In particular, we categorized existing research on sleep monitoring systems based on how the sensor is used, including the number and type of sensors, and the preferred position in the body. In addition to focusing on a specific system, issues concerning sleep monitoring systems such as privacy, economic, and social impact are also included. Finally, we presented an original sleep monitoring system solution developed in our laboratory. Results: By retrieving a large number of articles and abstracts, we found that hotspot techniques such as big data, machine learning, artificial intelligence, and data mining have not been widely applied to the sleep monitoring research area. Accelerometers are the most commonly used sensor in sleep monitoring systems. Most commercial sleep monitoring products cannot provide performance evaluation based on gold standard polysomnography. Conclusions: Combining hotspot techniques such as big data, machine learning, artificial intelligence, and data mining with sleep monitoring may be a promising research approach and will attract more researchers in the future. Balancing user acceptance and monitoring performance is the biggest challenge in sleep monitoring system research.

Homecare monitoring system: A technical proposal for the safety of the elderly experimented in an Alzheimer's care unit

Abstract: Today, the monitoring of dependent people is a real challenge. This is mainly due to the increase in the number of elderly and reduction of medical staff. However, works done in recent years in France are faced with obstacle of clinical and industrial validation. In this paper, we propose a monitoring system for dependent persons living alone at home or in an institution 24 h/24. This system is based on a presence multisensor network deployed in the living environment of the monitored person coupled with a wireless identification system. A learning algorithm is implemented in order to define a personalized behavioural model (motions deviation, nocturnal activity, falls, mobility). This model allows the nursing staff monitoring the behaviour through a web application accessed remotely, and also intervention in case of dangerous situations thanks to an alert system. In further, we describe the experiments conducted at the Caussade Local Hospital in France with Alzheimer patients and we present the results of data obtained. Finally, we propose the way for an economic model that would allow to industrialize the system with prospects of clinical validation on a larger cohort of patients.

Technology Studies to Meet the Needs of People With Dementia and Their Caregivers: A Literature Review

Abstract: The aim of this article is to present the findings of a review of studies that focused on technology supporting people with dementia and their caregivers. A literature search was carried out in eight scientific literature databases covering literature published between January 1992 and February 2007. A total of 46 studies providing original data and one review were included in this review. Analyses covered the aims of the studies, the technology used, study design, methods, outcome variables, and results. Most studies were carried out in residential care and focused on the needs of formal caregivers. Only a few studies involved people with dementia actively using the technology. The studies are difficult to compare because of the large variety of aims, technologies, design, and outcome measurements. There is a need for more research in this area, in particular, with people who have a mild stage dementia living in the community.

Towards pervasive computing in health care – A literature review

Abstract: The evolving concepts of pervasive computing, ubiquitous computing and ambient intelligence are increasingly influencing health care and medicine. Summarizing published research, this literature review provides an overview of recent developments and implementations of pervasive computing systems in health care. It also highlights some of the experiences reported in deployment processes. There is no clear definition of pervasive computing in the current literature. Thus specific inclusion criteria for selecting articles about relevant systems were developed. Searches were conducted in four scientific databases alongside manual journal searches for the period of 2002 to 2006. Articles included present prototypes, case studies and pilot studies, clinical trials and systems that are already in routine use. The searches identified 69 articles describing 67 different systems. In a quantitative analysis, these systems were categorized into project status, health care settings, user groups, improvement aims, and systems features (i.e., component types, data gathering, data transmission, systems functions). The focus is on the types of systems implemented, their frequency of occurrence and their characteristics. Qualitative analyses were performed of deployment issues, such as organizational and personnel issues, privacy and security issues, and financial issues. This paper provides a comprehensive access to the literature of the emerging field by addressing specific topics of application settings, systems features, and deployment experiences. Both an overview and an analysis of the literature on a broad and heterogeneous range of systems are provided. Most systems are described in their prototype stages. Deployment issues, such as implications on organization or personnel, privacy concerns, or financial issues are mentioned rarely, though their solution is regarded as decisive in transferring promising systems to a stage of regular operation. There is a need for further research on the deployment of pervasive computing systems, including clinical studies, economic and social analyses, user studies, etc.