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DR.BEAT ("Digital Research on Ballistocardiography for Extraterrestrial And Terrestrial use") develops a miniaturized sensor system with signal processing to interpret ballistocardiographic signals and implements an application oriented user interface. Presented is a breadboard prototype's functional tests with regard to data completeness and plausibility. The analysis confirmed a reliability of 99.99995% over the tests and the signals displayed the expected heart-specific characteristics. These results support the ethical justifiability of an initial study. [ABSTRACT FROM AUTHOR]

The ever-increasing flood of information, especially in the medical-clinical field, inter alia due to the increase of data-intensive mobile/wearable devices, is one of the biggest challenges of medical informatics. In this work different possibilities of the integration of wearable devices on the example of the development of a fall prevention system are presented and classified. We started with a commercial off-the-shelf one-on-one system (Shimmer/Arduino) using a Bluetooth connection, integrated via nurse call system as Human-Machine- Interface. During the evaluation of the system we mentioned several new requirements and optimization possibilities. Thus, we adjusted the hardware-software-system; the near-field communication was realized by IEEE802.15.4, we replaced commercial off-the-shelf devices with highly-specialized open hardware in-house developments and we transferred the nurse call integration by setting up our own network and integrating this into an existing (wireless) local area network. With this development, the energy-efficient, simple and intuitive mechanisms of proximity communication via IEEE802.15.4 can be combined with the benefits broadband functionalities, e.g. of Wi-Fi, with both worlds benefits and the compensation of some disadvantages. [ABSTRACT FROM AUTHOR]

DR.BEAT ("Digital Research on Ballistocardiography for Extraterrestrial And Terrestrial use") develops a miniaturized sensor system with signal processing to interpret ballistocardiographic signals and implements an application oriented user interface. Presented is a breadboard prototype's functional tests with regard to data completeness and plausibility. The analysis confirmed a reliability of 99.99995% over the tests and the signals displayed the expected heart-specific characteristics. These results support the ethical justifiability of an initial study.

Ballistocardiography is a method to gain detailed information about body movements imparted by the ballistic forces associated with cardiac contraction. We measured using different setups and sensor positions to gain information of a reference signal of healthy adults. We used two resting state recordings and two recordings under physical stress (ergometer and treadmill) with stepwise increasing load. Data was gathered from 34 subjects, which results in 72 data sets, overall, more than 18h of signal data. With these data we have created a first database for BCG reference. We started data analysis and created a first naive data representation prototype. Using this naive attempt, we created a user interface for the intuitive representation of live data as well as retrospective data.

Ballistocardiography (BCG) has gained more attention due to the fundamental goal of medical intervention in diagnostics and follow-up. BCG is particularly suitable for the study of heart failure, which a recent study has shown. The results of this working group shall be validated and reproduced with another study trial. Therefore, acceleration sensor prototypes will be placed on various parts of the patient's body and be connected to a computer unit, which allows a high data quality and high signal resolution. A temporal shift of only 20 ns ensures real-time measurement of BCG parameters. The reference measurement will be done with a 12-channel ECG. The study will include patients with heart failure. All conducted tests take place as part of the diagnostic-therapeutic routine. The only change in the procedure concerns the additional equipment with the measuring sensors. The results will be the validation of the data from the other working group, as well as the information about the choice of sensors and clock frequency, the measuring points and the needed features for early detection of heart failure in BCG signals.

The project SCARAB2 (Scalable, Robust and Adaptive on Board Ballistocardiography) aims to use Ballistocardiography (BCG) to monitor flight passengers. In order to show that recorded BCG data from flights give evaluable information even in the noisy environment of an airplane, we monitored a heart-healthy passenger using BCG. Furthermore, we show that there can be a conclusion to heart activities from the recorded ballistocardiogram by comparing the data to a concurrently recorded electrocardiogram (ECG).

With regard to the growing number of older adults, it needs smart solutions for fall prevention. Especially at geriatric institutions, the risk of falling is very high and frequently leads to injuries, resulting in serious consequences. We present the Inexpensive Node for Bed Exit Detection (INBED), a comprehensive signaling system for fall prevention. The INBED system is based on a wireless sensor network infrastructure via IEEE802.15.4 and highly-specialized open hardware in-house developed wearable. The device, which will be attached to the patients, can detect several types of movement. Occurring events are forwarded to the nursing staff immediately by using the self-organizing and scalable network including wide area network integration. The system can help to relieve the staff while the personal freedom of movement and privacy of patients is increased. With this development, the energy-efficient, simple and intuitive mechanisms of proximity communication can be combined with broadband benefits.