The 1st Workshop on Embedded Sensor Systems for Health through Internet of Things (ESS-H IoT)
A brief description of the specific technical issues that the workshop will address:
The healthcare sector is under change, and the sector of distributed healthcare/home healthcare is increasing, enabled by new technology. Elderly will keep on living in their homes, but with a need of aids. One of the ultimate goals is the self-serve, independence and dignity enhancement of seniors through innovative ICT-based solutions. Another trend is to monitor not one but several parameters in order to gain a more holistic appreciation of the person/patient. This is further accentuated by the prospects of multi-morbid patients: several diseases and their interactions require monitoring of multiple parameters. Also, each patient reacts individually, and the systems need to be individually adaptable. Healthcare is also foreseen to go from treating acute conditions to providing preventive actions. As an example, many chronic diseases are to a large extent possible to prevent by changes of lifestyle. This makes long-term monitoring of multiple physiological parameters a technology holding large expectations, and that monitoring will change focus from patient surveillance into being a support for a healthier lifestyle. This shows the necessity of Embedded Sensor Systems for Health through Internet of Things (ESS-H IoT),
Embedded Sensor Systems for Health (ESS-H), is aiming to provide monitoring of patients in their home environment by wearable, wireless sensor systems. These sensor systems enable monitoring with minor instruction, and allow the monitored person to continue with normal life activities. Within ESS-H, one of the main focus is on sensor systems that can provide reliable data acquisition for chronically diseased patients. The acquisition should be adaptive and reconfigurable, thus allowing request for certain signals to start if required, and for more essential signals to gain higher priority. This means supporting dynamic priority capture and data flow. Adaptive data acquisition means that the system itself can adapt to what it records or to the environment, for example an arrhythmia might trigger the start of recording a full-scale ECG. Further, the priority of for example an arrhythmia might suppress the monitoring of less important parameters, such as body temperature. Reconfigurable data acquisition means that depending on the situation and the environment, the system can be reconfigured to measure other parameters or in another way.
Similarly, Internet of Things (IoT) requires dependable wireless communication: the communication from sensors to a communication gateway, and the communication from gateway to a dependable data storage facility. The communication from sensors to communication gateway is a local communication where the main scientific problems are two: finding and assuring a communication path from sensor to gateway, and compensating for local electromagnetic disturbances. These two problems are interconnected; assuring a communication path requires the ability to compensate for electromagnetic disturbances. From a scientific point of view, assuring a communication path can be seen mainly as a routing problem, while compensating for electromagnetic disturbances can be seen mainly as a coding and radio problem. Since sensor nodes in the health area often can be worn, energy conservation is also an important factor to consider. The communication from gateway to data storage has its main problem in keeping and guaranteeing connectivity in spite of variations in communication technology availability. This is mainly a network diversity problem, where multiple networks are used to compensate for variations in availability.
Designing and developing an embedded sensor system for health is a complex task that requires sophisticated engineering activities to be accomplished. One of the most central and the far most costly activity is to investigate a product to ensure stakeholders of its quality, as ultimately human lives may depend on the correct functioning of an embedded sensor system for health. The validation and verification for the embedded sensor system(s) typically amount to 40-60% of the total development effort for industrial products. The most commonly applied technique for validation and verification is testing. In testing embedded sensor systems for health, the main challenges are to test a number of dependability properties, such as a timeliness, efficiency, and safety, and to be able to model, analyze and perform testing of systems not only consisting of hardware and software but also including humans.
The reasons why the workshop is interesting and timely:
This workshop aims at using embedded sensor systems in health monitoring applications, considering the future vision of Internet of Things. It covers a variety of research directions, such as; sensor hardware development, wireless communication and signal processing. Designing medical sensors with appropriate radios enables fast observation of physiological data. A wireless communication provides the facility to forward the sensing data through a reliable medium to the destination. Finally, applying signal processing algorithms contribute in continuous patient/elderly monitoring and fast clinical deterioration detection.
A call for papers, including the workshop submission deadlines:
Call for Papers
Embedded sensor systems for health monitoring deals with data acquisition, signal processing and decision support for use in sensor systems aimed at health monitoring. Applying Internet of Things (IoT), as existing technologies can provide physiological data management facilities deals with infrastructure requirements for safe and secures management of interconnected devices and data. In addition to the Call for Scientific Papers HealthyIoT 2015, this workshop offers an opportunity for international researchers to present and discuss their ongoing work within the workshop.
This 1st Workshop on Embedded Sensor Systems for Health and Internet of Things (ESS-H IoT) aims to:
- to discuss work in progress and explore opportunities for new research related to a topic of interest.
- provide a forum for identifying important contributions and opportunities for research on ESS-H IoT,
- showcase applications of Embedded sensor systems for health.
Topics of interest include (but are not limited to):
- Wearable sensor systems
- Medical and sensor data stream processing
- Signal processing and analysis
- Machine learning for signal processing
- Cloud Technologies for Healthcare
- Intelligent data processing and predictive algorithms in eHealth
- Telemedicine applications
- Network communications for health monitoring
- Security, Safety and Privacy in IoT
- Mobile sensing and smartphone sensing
- Wireless sensor and actuator networks
- Sensor network operating systems and resource management
Submissions should be original papers that have not already been published elsewhere. However, papers may include previously published results that support a new theme, as long as all past publications are fully referenced.
Submitted papers will be peer-reviewed and selected on the basis of these reviews. Accepted papers will be presented at the workshop.
- Submission Deadline: August 10th, 2015
- Notification Date: 31st August, 2015
- Camera-Ready Deadline: 7th September, 2015
- Workshop Date: 26th October 2015
Tentative composition of the organizing and program committees:
Mobyen Uddin Ahmed, Mälardalen University, Sweden
Hossein Fotouhi, Mälardalen University, Sweden
Shahina Begum, Mälardalen University, Sweden
Mats Björkman, Mälardalen University, Sweden
Maria Lindén, Mälardalen University, Sweden
Hamid GholamHosseini, Auckland University of Technology, New Zealand
Miguel Angel Valero, Ministerio de Sanidad, Servicios Sociales e Igualdad, Spain
Mário Alves, Polytechnic Institute of Porto (ISEP/IPP), Portugal
Anis Koubâa, Prince Sultan University, Saudi Arabia
Ramiro Martinez de Dios, University of Seville, Spain
Shashi Prabh, Shiv Nadar University, India
Carlo Alberto Boano, TU Graz, Austria
Stefano Tennina, University of L'Aquila, Italy
Behnam Dezfouli, University of Iowa, USA
Nouha Baccour, University of Sfax, Tunisia