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Shimmer at BSN 2014

The 11th Annual Body Sensor Networks Conference 2014 is taking place on June 16-19 in Zurich, Switzerland, and Shimmer will be in attendance to showcase our broad range of wearable sensing capabilities.

The 2014 International Conference on Wearable and Implantable Body Sensor Networks (BSN 2014) will provide a unique forum for researchers and industry practitioners to discuss the latest work in various fields utilizing body sensor networks. Building on the success of the previous 10 annual meetings, the 11th BSN conference will be held at the Swiss Federal Institute of Technology (ETH Zurich) in Zurich, Switzerland.

Shimmer will be hosting a workshop at the event, on Thursday, 19th June, and we will also be available at our booth during the two main conference days. Members of the Shimmer team will be on hand to demonstrate our full range of wireless sensing hardware and supporting applications, and to answer any questions that visitors may have.

We will be demonstrating the new Shimmer3 sensing platform, modules, accessories, and new applications. Attendees will have the chance to see, and interact with, the latest applications and features of the Shimmer platform, and to discuss their use cases with our engineers.

Come to our Workshop at BSN – Composing Sensing Systems with Shimmer3

On Thursday 19th June at 2pm, Shimmer will host a workshop, demonstrating to current and prospective Shimmer users, how they can use the Shimmer platform to create custom sensing solutions in clinical, mobile, or longitudinal study settings. We will cover all aspects of development with Shimmer3, from firmware implementation, and algorithm development, through to data collection and host-side software applications.

The workshop will be led by Niamh O’Mahony, Lead Applications Engineer, Shimmer, and will include invited presentations from existing Shimmer3 users. The following abstracts provide a sneak preview into the topics you can expect to hear more about:

Activity Routine Discovery in Stroke Rehabilitation Patients using Shimmer3 Motion Sensors

Julia Seiter, Wearable Computing Lab., Swiss Federal Institute of Technology (ETH) Zurich, Switzerland.

Information about activity routines stroke patients perform in their daily life could add valuable information to personal therapy goals during the rehabilitation process. The talk introduces our framework to discover patients’ daily life activity routines using body-worn Shimmer3 motion sensors. We monitored stroke rehabilitation patients in a day care center during several weeks. Besides the system setup the talk will highlight the study design and introduce our topic model based approach for activity routine discovery from upper and lower extremity motion sensor data.

Assessing Performance in Psychiatric Patients

Prof. Antonio Artés Rodríguez, Department of Signal Theory and Communications, Universidad Carlos III de Madrid (UC3M), Madrid, Spain.

There are two ways to assess functional outcomes in psychiatric patients: capacity (what a person can do under optimal conditions) versus performance (what a person actually does under real world conditions). Capacity is assessed in a controlled setting, using behavioural tasks. Performance is commonly assessed using self-reports from the patient or caregiver, by direct observation of the patient, or from reports by high-contact clinicians, all of them subject to one way or another of bias. In this work we propose to assess performance by automatically recognizing the activity the patient is performing. Using a single Shimmer3 IMU sensor per patient, we have developed a person independent Human Activity Recognition (HAR) system and a histogram-based daily activity representation. The system has been designed for caregiver operation and it can collect the information from multiple patients. The system is now being tested with patients that suffer from mood and schizophrenic disorder using daily recording from 9:30 to 23:00 in a hospital unit, and will be extended for ambulatory monitoring.

Development of an Inertial Sensor Based Stepping Exergame for Elderly

Alan Bourke, PhD., Laboratory of Movement Analysis and Measurement (LMAM), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

It has recently been shown that exergaming can increase exercise adherence and uptake in an elderly population thus reducing the risk of falling, the motivation to develop virtual reality based exercise interventions is thus warranted. However in-order to develop such an intervention, certain criteria needs to be considered. The minimum requirement for these exergames is that they should be fun and engaging as well as challenging and safe. We present the design elements and challenges involved in bringing a virtual reality based stepping exercise intervention from concept through to reality.

This exergame, developed in the framework of the FARSEEING project, allows the user to interact with a three dimensional graphical environment, which is projected in their field of vision. Direction is given via visual feedback to the user on which target to virtually contact with a virtual representation of their feet in the form of an avatar. The user’s feet movements are tracked using the Shimmer inertial sensors which measure true displacement of the feet in real-time and used as input to the game engine.

In order to develop such an exergame a number of technical computational and algorithmic challenges needed to be addressed. We present the technical requirements for the system, including the interface, processing unit, sensors and communication. We also cover the animation, safety and intervention design including the taxonomy and the implemented system for the final virtual reality exergame.

Understanding Gait Information using Inertial Sensors

Dr. Matthew Patterson, Insight Centre for Data Analytics, University College Dublin (UCD), Dublin, Ireland.

The line of work I will be presenting is around the use of inertial sensors to measure walking gait. Half of the presentation will describe the development of novel processing techniques termed feature extraction. These techniques were used to identify pathological gait patterns which traditional spatio-temporal parameters could not identify. The second half of the presentation will discuss the use of inertial sensors to measure gait patterns in the home and community setting and the implications of attempting to interpret data from an unconstrained, unsupervised environment.

We hope to see you there!

To contact us in advance or to confirm your attendance at the workshop, please email us – we would be happy to meet you there!

To register for the event, please see the BSN website at


July Update on BSN

Congratulations to our competition winner at BSN this year, Brit Maike Quandt from EMPA - Swiss Federal Labs for Materials Science and Technology. All entrants were in with a chance to win a tablet, so thank you to those who entered.