In this work, we present the design and implementation of a micro watt level power consumption, human body capacitance based sensor for recognizing and counting gym workouts. The concept also works when the device is attached to a body part which is not directly involved in the activity's movement. In contrast, most of the widely used motion sensing based approaches require placing the sensor on the moving body part (e.g. for analyzing leg based gym exercises the sensor needs to be placed on the leg). We described the physical principle behind the ubiquitous electric coupling between human body and environment, and explored the capability of this sensing modality in gym workouts. We evaluated our sensor with 11 subjects, performing 7 popular gym workouts each day over 5 days with our sensor being placed at 3 different body positions, including a non-contact position, where the sensor is placed in the subject's pocket. Results showed that our sensing approach achieved an average counting accuracy of 91%, which is highly competitive with commercial devices on the market. The mean leave one user out workout recognition f-scores obtained were of 63%, 56%, 45% for sensors located on wrist, on calf and in pocket, respectively. As every subject performed activities over multiple days changing shoe height, shoe and clothes type, we demonstrate that full body activity counting and to some extent recognition is feasible, regardless of personal habit of movement speed and scale.

This video paper describes the practical outcome of the first milestone of a project aiming at setting up a so-called Hybrid Team that can accomplish a wide variety of different tasks. In general, the aim is to realize and examine the collaboration of augmented humans with autonomous robots, virtual characters and SoftBots (purely software based agents) working together in a Hybrid Team to accomplish common tasks. The accompanying video shows a customized packaging scenario and can be downloaded from http://hysociatea.dfki.de/?p=441.

We demonstrate that a cheap (30USD) small, low power 8x8 thermal sensor array can by itself provide a broad range of information relevant for human activity monitoring in home and office environments. In particular the sensor can track people with an accuracy in the range of 1m (which is sufficient to recognize activity relevant regions), detect the operation mode of various appliances such as toaster, water cooker or egg cooker and actions such as opening a refrigerator, the oven or taking a shower. While there are sensing modalities for each of the above types of information (e.g. current sensors for appliances) the fact that they can all be detected by such a simple sensor is highly relevant for practical activity recognition systems. Compared to vision (or thermal imaging systems) the system has the advantage is being less privacy invasive allowing it for example to monitor bathroom activities (as shown in one of our evaluation scenarios). The paper describes the sensor, the methods used for activity detection and the evaluation.

Emerging areas of body sensor networks (BSNs) include closed-loop applications with the need for a frequent exchange of sensor data between implanted and/or body-worn devices. An example is the Artificial Accommodation System, a set of two micro-mechatronic systems implanted into the capsular bags of the eyes, which require continuous exchange of sensor data at 10 Hz. This paper will present a light-weight medium access control (MAC) protocol capable of synchronising two sensor nodes through the cyclic dissemination of regular data messages and time stamping on MAC layer on the receiver side. The inter-arrival time of two messages is used to successively predict the time of arrival of a future message. Thus, idle listening, which is a major source of energy wastage in time division multiple access (TDMA) protocols, can be reduced to a minimum just dependent on the underlying clock accuracy of the system without requiring additional protocol overhead for synchronisation purposes. The protocol was implemented in an experimental setup of the Artificial Accommodation System using off-the-shelf components. Due to space restrictions, the internal RC oscillators of standard microcontrollers were employed as clock sources. Despite their low frequency accuracy, remarkably low duty cycles below 0.6% were obtained for a bidirectional data exchange of 8-byte messages at 10 Hz and 250 kbit/s.