Automated Heart Rate Detection in Seismocardiograms Using Electrocardiogram-Based Algorithms-A Feasibility Study.

In recent decades, much work has been implemented in heart rate (HR) analysis using electrocardiographic (ECG) signals. We propose that algorithms developed to calculate HR based on detected R-peaks using ECG can be applied to seismocardiographic (SCG) signals, as they utilize common knowledge regarding heart rhythm and its underlying physiology. We implemented the experimental framework with methods developed for ECG signal processing and peak detection to be applied and evaluated on SCGs. Furthermore, we assessed and chose the best from all combinations of 15 peak detection and 6 preprocessing methods from the literature on the CEBS dataset available on Physionet. We then collected experimental data in the lab experiment to measure the applicability of the best-selected technique to the real-world data; the abovementioned method showed high precision for signals recorded during sitting rest (HR difference between SCG and ECG: 0.12 ± 0.35 bpm) and a moderate precision for signals recorded with interfering physical activity-reading out a book loud (HR difference between SCG and ECG: 6.45 ± 3.01 bpm) when compared to the results derived from the state-of-the-art photoplethysmographic (PPG) methods described in the literature. The study shows that computationally simple preprocessing and peak detection techniques initially developed for ECG could be utilized as the basis for HR detection on SCG, although they can be further improved.

DR.BEAT: First Insights into a Study to Collect Baseline BCG Data with a Sensor-Based Wearable Prototype in Heart-Healthy Adults.

The DR.BEAT project aims at the further development of a measurement system for recording ballistocardiographic signals into a body-worn sensor system combined with extensive signal processing, data evaluation and visualization. With a first breadboard prototype, an explorative feasibility study for acquiring initial signals of healthy cardiac activity in adults was performed. This paper briefly presents the DR.BEAT project, the breadboard prototype, the study conducted, and initial insights into the study results. The signals obtained in the study exhibit the seismocardiographic characteristics as reported in the literature and form the basis for further development of the hardware as well as the pre-processing and automated analysis algorithms in the DR.BEAT project.Clinical Relevance- The characteristics of ballisto- and seismocardiographic signals allow to infer about the mechanical work of the heart. The development of a body-worn sensor system to record ballisto- and seismocardiographic signals, compact enough for everyday wear, enables the acquisition of heart-specific parameters in terrestrial as well as extraterrestrial application scenarios. Combined with extensive signal analysis and visualization, it holds the potential to monitor heart health in a variety of contexts and support its maintenance and improvement.

On-Site Visualization of Ballistocardiography Data.

We describe the background, features and functions of a custom application for the acquisition, live presentation, and convenient recording of ballistocardiography data acquired by external accelerometric sensors.

Time Bias Awareness in ECG-Based Multiple Source Data Matching.

For cardiological datasets acquired via different methodologies, ECG signals that are recorded in parallel allow for relatively accurate matching. Some research issues, e.g., the identification of timings of the cardiac cycle in seismocardiography, require higher temporal resolutions. Therefore, we introduce a method derived from a feasibility study to determine deviations and factors influencing the merging of signals simultaneously recorded with different modalities.

Beat to BEAT - Non-Invasive Investigation of Cardiac Function on the International Space Station.

This paper describes the protocol of the microgravity experiment BEAT (Ballistocardiography for Extraterrestrial Applications and Long-Term Missions). The current study makes use of signal acquisition of cardiac parameters with a high-precision Ballistocardiography (BCG)/Seismocardiography (SCG) measurement system, which is integrated in a smart shirt (SmartTex). The goal is to evaluate the feasibility of this concept for continuous wearable monitoring and wireless data transfer. BEAT is part of the "Wireless Compose-2" (WICO2) project deployed on the International Space Station (ISS) that will provide wireless network infrastructure for scientific, localization and medical experiments.

Seismocardiography with Smartphones: No Leap from Bench to Bedside (Yet).

For a decade, seismocardiography (SCG) on smartphones has been an interesting topic within the technical community, but mobile applications for this topic are rare on the market. The transition from laboratory to bedside application seems to have not yet been completed. To possibly increase the chances of a successful implementation, the added value of the method needs to be addressed clearly and backed up by research. The authors address the following aspects. 1. To improve comparability, standardization is required, 2. adequate validation processes in clinical settings will build trust, but foremost, 3. the field of application should be critically evaluated to identify the most meaningful and reasonable benefit of this method.

Development of a Presentation Interface for Seismo- and Ballistocardiographic Data.

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.

A Structured Measurement of Highly Synchronous Real-Time Ballistocardiography Signal Data of Heart Failure Patients.

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.

Wireless Sensor Network for Fall Prevention on Geriatric Wards: A Report.

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.

First Feasibility Analysis of Ballistocardiography on a Passenger Flight.

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).

INBED: A Highly Specialized System for Bed-Exit-Detection and Fall Prevention on a Geriatric Ward.

OBJECTIVE: In geriatric institutions, the risk of falling of patients is very high and frequently leads to fractures of the femoral neck, which can result in serious consequences and medical costs. With regard to the current numbers of elderly people, the need for smart solutions for the prevention of falls in clinical environments as well as in everyday life has been evolving. METHODS: Hence, in this paper, we present the Inexpensive Node for bed-exit Detection (INBED), a comprehensive, favourable signaling system for bed-exit detection and fall prevention, to support the clinical efforts in terms of fall reduction. The tough requirements for such a system in clinical environments were gathered in close cooperation with geriatricians. RESULTS: The conceptional efforts led to a multi-component system with a core wearable device, attached to the patients, to detect several types of movements such as rising, restlessness and-in the worst case-falling. Occurring events are forwarded to the nursing staff immediately by using a modular, self-organizing and dependable wireless infrastructure. Both, the hardware and software of the entire INBED system as well as the particular design process are discussed in detail. Moreover, a trail test of the system is presented. CONCLUSIONS: The INBED system can help to relieve the nursing staff significantly while the personal freedom of movement and the privacy of patients is increased compared to similar systems.

Comparison and validation of capacitive accelerometers for health care applications.

Fall detection, gait analysis and context recognition are examples of applications where capacitive accelerometers are widely used in health care. In most of the existing work, algorithms were developed for a specific platform and accelerometers were used without explicitly choosing a specific type. With this work we present an inexpensive and practical test setup for replicable and repeatable testing of accelerometers. In addition we use this setup to evaluate six of the most commonly available accelerometers today and list their outcomes for linearity, power consumption and correlation of the tested sensors. We also attempt to an answer to the question of whether applications and algorithms developed for one platform and one type of accelerometer can be easily transferred to another accelerometer.