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This paper presents a wearable sensor architecture for frequency-multiplexed electrical impedance tomography (EIT) and synchronous multilead electrocardiogram (ECG) data acquisition. The system is based on a novel electronic sensing architecture, called cooperative sensors, that significantly reduces the cabling complexity and enables flexible EIT stimulation and measurement patterns. The cooperative-sensor architecture was initially designed for ECG and has been extended for multichannel bioimpedance measurement. This approach allows for an adjustable EIT stimulation pattern via frequency-division multiplexing. This paper also shows a calibration procedure as well as EIT system noise performance assessment. Preliminary measurements on a healthy volunteer showed the ability of the wearable system to measure EIT data synchronously with multilead ECG. Ventilation-related and heartbeat-related EIT images were reconstructed, demonstrating the feasibility of the proposed architecture for non-invasive cardiovascular monitoring.

Classical approaches for measuring high-quality ECG require the use of gel electrodes and individually shielded cables, which limit patient comfort, especially in long-term use. We recently introduced a novel sensing architecture-so-called cooperative sensors-that allow the use of active dry electrodes connected by two unshielded wires. The aim of this work is to qualitatively evaluate an ECG recorded with a dry-electrode cooperative-sensor system. To that end, preliminary observations were made on three healthy subjects. The ECGs were concurrently recorded with cooperative sensors and a gold-standard 12-lead ECG device during a stress test on a stationary bicycle. First experimental measurements demonstrated the reliability of the approach for a wearable 12-lead ECG monitoring system tested in real settings.

The diagnosis of respiratory diseases relies largely on auscultation. To further improve the diagnosis quality, continuous acoustic multi-channel surveillance of the airways is highly desirable. The application of multiple sensors around the thorax implies size and cost constraints for the sensors. In this article we first report on the design and development of a wearable and low-cost electronic stethoscope which is easy to integrate in a garment. We then analyzed the noise and linearity of the recorded sound signal and benchmarked a prototype with a standard stethoscope which is widely used in clinical practice.

Lung sounds acquired by stethoscopes are extensively used in diagnosing and differentiating respiratory diseases. Although an extensive know-how has been built to interpret these sounds and identify diseases associated with certain patterns, its effective use is limited to individual experience of practitioners. This user-dependency manifests itself as a factor impeding the digital transformation of this valuable diagnostic tool, which can improve patient outcomes by continuous long-term respiratory monitoring under real-life conditions. Particularly patients suffering from respiratory diseases with progressive nature, such as chronic obstructive pulmonary diseases, are expected to benefit from long-term monitoring. Recently, the COVID-19 pandemic has also shown the lack of respiratory monitoring systems which are ready to deploy in operational conditions while requiring minimal patient education. To address particularly the latter subject, in this article, we present a sound acquisition module which can be integrated into a dedicated garment, thus, minimizing the role of the patient for positioning the stethoscope and applying the appropriate pressure. We have implemented a diaphragm-less acousto-electric transducer by stacking a silicone rubber and a piezoelectric film to capture thoracic sounds with minimum attenuation. Furthermore, we benchmarked our device with an electronic stethoscope widely used in clinical practice to quantify its performance.

The WELCOME system is an innovative telemonitoring system designed to provide constant monitoring of COPD patients also suffering from other major comorbidities. It consists of a sensors vest capable of recording various vital parameters in real time and transmitting them to the cloud via a tablet PC and wireless connection. In addition, peripheral devices record extra physiological data which is coupled with responses to validated health questionnaires that the patient responds to via the tablet. A dedicated medical decision support system (DSS) and a medical professional user interface support the system in providing automated detection of abnormal conditions. The obtained signals included Heart and Respiratory Rate, Body Posture, SpO2, multi-lead ECG, Auscultation and Electric Impedance Tomography. The system is tested with pilot studies in two European countries, Greece and UK. The preliminary results from the Greek pilot study are presented in this paper, highlighting the main findings from the first operational use of the WELCOME infrastructure.

Classical approaches to make high-quality measurements of biopotential signals require the use of shielded or multiwire cables connecting the electrodes to a central unit in a star arrangement. As a consequence, increasing the number of leads increases cabling and connector complexity, which is not only limiting the patient comfort but is also anticipated as the main limiting factor to future miniaturization and cost reduction of tomorrow's wearables. We have recently introduced a novel sensing architecture that significantly reduces the cabling complexity by eliminating shielded or multiwire cables and by allowing simple connectors, thanks to a bus arrangement. In this architecture, electrodes are replaced by so-called cooperative sensors that require synchronous operation for systems larger than two sensors. This paper presents a novel full duplex body-sensor network based on a simple two-wire bus that combines biopotential measurements, synchronization, and gathering of data in a single cooperative sensor with a throughput up to 2 Mb/s. When compared to others, the suggested approach is advantageous as it keeps the cabling complexity at its minimum and does not require every sensor to be equipped with wireless communication capabilities. First experimental measurements demonstrated the reliability of the approach for a wearable 12-lead electrocardiogram monitoring system tested in real-life scenario.

Many cardiorespiratory physiological signals can be measured from the chest skin. When measured at many spots, some of them like EIT (Electrical Impedance Tomography) produce images. Classical approaches cannot practically be used to make wearables with a large number of sensors, because the sensing points are connected to a bulky centralized electronics box in a star arrangement. The solution is to use cooperative sensors. A vest embedding 51 multi-signal sensors designed for COPD (Chronic Obstructive Pulmonary Disease) patients is described as example.

Integrated care of patients with COPD and comorbidities requires the ability to regard patient status as a complex system. It can benefit from technologies that extract multiparametric information and detect changes in status along different axes. This raises the need for generation of systems that can unobtrusively monitor, compute, and combine multiorgan information. In this paper, the concept and ongoing work for such an approach is presented as regards the multiple types of data recorded, features extracted, and examples of how they are combined in the EU-funded project WELCOME (Wearable Sensing and Smart Cloud Computing for Integrated Care to COPD Patients with Comorbidities) [1], for the integrated management of COPD and comorbidities.

There have been significant advances in Technology enabled care (TEC) including wearable technology. However, to our knowledge, there is a paucity of literature related to patient perceptions of smart wearable sensors. The WELCOME platform (FP-7 funded project) is an innovative integrated system using wearable sensors and smart computing for COPD patients with co-morbidities. 1 The aim of this platform is the early diagnosis of exacerbations and disease deterioration allowing for early intervention. The wearable sensors in this project have been integrated into a vest (Figure 1) and several prototypes with mock sensors were developed. A structured interview was designed to explore COPD patient perceptions pertaining to vest comfort, ease of wear and handling, willingness to use and concerns. Interviews were designed to take place at the clinic (England and Netherlands) where patients are provided with a suitably sized vest to try on followed by the structured interviews. To date, 15 interviews have been completed at Croydon Healthcare services Trust, and the Dutch interviews are underway. Results The interview transcripts were thematically analysed using mostly framework analysis. Analysis was conducted using NVIVO 10. The following themes emerged from the data.1) Acceptance of vest 2) willingness to wear the vest during daytime 3) Discomfort with sensor size and shape prohibiting night wear 4) Demonstrated capability of donning the vest and handling of the sensors 5) Safety concerns emphasising importance of patient education before use 6) Gender related concerns regarding vest design. Conclusion The vests were well received by patients however the above results illustrate the importance of involving the end users in the design and development of any smart intervention. These results will be used for the final design and development of the vest. Reference 1 Chouvarda I, Philip NY, Natsiavas P, et al . WELCOME-innovative integrated care platform using wearable sensing and smart cloud computing for COPD patients for comorbidities. Conf Proc IEEE Eng Med Biol Soc . 2014; 2014 :3180–3. doi: 10.1109/EMBC.2014.6944298

Objective Development of wearable medical technology for remote monitoring of patients suffering from chronic lung diseases may improve the care, therapy and outcome of these patients. Approach A multimodal system using wearable sensors for the acquisition of multiple biosignals (electrical bioimpedance of the chest for electrical impedance tomography and respiratory rate assessment, peripheral oxygen saturation, chest sounds, electrocardiography for heart rate measurement, body activity, and posture) was developed and validated in a prospective, monocentric study on 50 healthy subjects. The subjects were studied under different types of ventilation (tidal and deep breathing, forced full expiration maneuver) and during increased body activity and posture changes. The major goals were to assess the functionality by determining the presence and plausibility of the signals, comfort of wearing and safety of the vest. Main results All intended signals were recorded. Streaming of selected signals and wireless download of complete data sets were functional. Electrical impedance tomography recordings revealed good to excellent quality of detection of ventilation-related impedance changes in 34 out of 50 participants. Respiratory and heart rates were reliably detected and generally in physiological ranges. Peripheral oxygen saturation values were unphysiologically low. The chest sound recordings did not show waveforms allowing meaningful analysis of lung sounds. Body activity and posture were correctly identified. The comfort of wearing and the vest properties were positively rated. No adverse events occurred. Significance Albeit the full functionality of the current vest design was not established, the study confirmed the feasibility of remote functional chest monitoring with a marked increase in clinically relevant information compared to existing systems.