The NEVERMIND e-health system in the treatment of depressive symptoms among patients with severe somatic conditions: A multicentre, pragmatic randomised controlled trial.

Background: This study assessed the effectiveness of the NEVERMIND e-health system, consisting of a smart shirt and a mobile application with lifestyle behavioural advice, mindfulness-based therapy, and cognitive behavioural therapy, in reducing depressive symptoms among patients diagnosed with severe somatic conditions. Our hypothesis was that the system would significantly decrease the level of depressive symptoms in the intervention group compared to the control group. Methods: This pragmatic, randomised controlled trial included 425 patients diagnosed with myocardial infarction, breast cancer, prostate cancer, kidney failure, or lower limb amputation. Participants were recruited from hospitals in Turin and Pisa (Italy), and Lisbon (Portugal), and were randomly assigned to either the NEVERMIND intervention or to the control group. Clinical interviews and structured questionnaires were administered at baseline, 12 weeks, and 24 weeks. The primary outcome was depressive symptoms at 12 weeks measured by the Beck Depression Inventory II (BDI-II). Intention-to-treat analyses included 425 participants, while the per-protocol analyses included 333 participants. This trial is registered in the German Clinical Trials Register, DRKS00013391. Findings: Patients were recruited between Dec 4, 2017, and Dec 31, 2019, with 213 assigned to the intervention and 212 to the control group. The sample had a mean age of 59·41 years (SD=10·70), with 44·24% women. Those who used the NEVERMIND system had statistically significant lower depressive symptoms at the 12-week follow-up (mean difference=-3·03, p<0·001; 95% CI -4·45 to -1·62) compared with controls, with a clinically relevant effect size (Cohen's d=0·39). Interpretation: The results of this study show that the NEVERMIND system is superior to standard care in reducing and preventing depressive symptoms among patients with the studied somatic conditions. Funding: The NEVERMIND project received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 689691.

A protocol for a multicentre, parallel-group, pragmatic randomised controlled trial to evaluate the NEVERMIND system in preventing and treating depression in patients with severe somatic conditions.

BACKGROUND: Depressive symptoms are common in individuals suffering from severe somatic conditions. There is a lack of interventions and evidence-based interventions aiming to reduce depressive symptoms in patients with severe somatic conditions. The aim of the NEVERMIND project is to address these issues and provide evidence by testing the NEVERMIND system, designed to reduce and prevent depressive symptoms in comparison to treatment as usual. METHODS: The NEVERMIND study is a parallel-groups, pragmatic randomised controlled trial to assess the effectiveness of the NEVERMIND system in reducing depressive symptoms among individuals with severe somatic conditions. The NEVERMIND system comprises a smart shirt and a user interface, in the form of a mobile application. The system is a real-time decision support system, aiming to predict the severity and onset of depressive symptoms by modelling the well-being condition of patients based on physiological data, body movement, and the recurrence of social interactions. The study includes 330 patients who have a diagnosis of myocardial infarction, breast cancer, prostate cancer, kidney failure, or lower limb amputation. Participants are randomised in blocks of ten to either the NEVERMIND intervention or treatment as usual as the control group. Clinical interviews and structured questionnaires are administered at baseline, at 12 weeks, and 24 weeks to assess whether the NEVERMIND system is superior to treatment as usual. The endpoint of primary interest is Beck Depression Inventory II (BDI-II) at 12 weeks defined as (i) the severity of depressive symptoms as measured by the BDI-II. Secondary outcomes include prevention of the onset of depressive symptoms, changes in quality of life, perceived stigma, and self-efficacy. DISCUSSION: There is a lack of evidence-based interventions aiming to reduce and prevent depressive symptoms in patients with severe somatic conditions. If the NEVERMIND system is effective, it will provide healthcare systems with a novel and innovative method to attend to depressive symptoms in patients with severe somatic conditions. TRIAL REGISTRATION: DRKS00013391. Registered 23 November 2017.

Multimodal remote chest monitoring system with wearable sensors: a validation study in healthy subjects.

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.

Qualitative investigation into a wearable system for chronic obstructive pulmonary disease: the stakeholders' perspective.

OBJECTIVES: To ascertain the stakeholders' views and devise recommendations for further stages of the Wearable Sensing and Smart Cloud Computing for Integrated Care to Chronic Obstructive Pulmonary Disease (COPD) Patients with Co-morbidities (WELCOME) system development. This system aims to create a wearable vest to monitor physiological signals for patients concerned incorporating an inhaler adherence monitoring, weight, temperature, blood pressure and glucose metres, and a mobile health application for communication with healthcare professionals (HCPs). DESIGN: A study of qualitative data derived from focus groups and semistructured interviews. SETTING: 4 participating clinical sites in Greece, the UK, Ireland and the Netherlands. PARTICIPANTS: Purposive sampling was used to recruit 32 patients with COPD with heart failure, diabetes, anxiety or depression, 27 informal carers and 23 HCPs from 4 European Union (EU) countries for focus groups and interviews. RESULTS: Most patients and HCPs described the WELCOME system as 'brilliant and creative' and felt it gave a sense of safety. Both users and HCPs agreed that the duration and frequency of vest wear should be individualised as should the mobile application functions. The parameters and frequency of monitoring should be personalised using a multidisciplinary approach. A 'traffic light' alert system was proposed by HCPs for abnormal results. Patients were happy to take actions in response. CONCLUSIONS: WELCOME stakeholders provided valuable views on the development of the system, which should take into account patient's individual comorbidities, circumstances and concerns. This will enable the development of the individualised system in each member state concerned.

Wearable Textile Platform for Assessing Stroke Patient Treatment in Daily Life Conditions.

Monitoring physical activities during post-stroke rehabilitation in daily life may help physicians to optimize and tailor the training program for patients. The European research project INTERACTION (FP7-ICT-2011-7-287351) evaluated motor capabilities in stroke patients during the recovery treatment period. We developed wearable sensing platform based on the sensor fusion among inertial, knitted piezoresistive sensors and textile EMG electrodes. The device was conceived in modular form and consists of a separate shirt, trousers, glove, and shoe. Thanks to the novel fusion approach it has been possible to develop a model for the shoulder taking into account the scapulo-thoracic joint of the scapular girdle, considerably improving the estimation of the hand position in reaching activities. In order to minimize the sensor set used to monitor gait, a single inertial sensor fused with a textile goniometer proved to reconstruct the orientation of all the body segments of the leg. Finally, the sensing glove, endowed with three textile goniometers and three force sensors showed good capabilities in the reconstruction of grasping activities and evaluating the interaction of the hand with the environment, according to the project specifications. This paper reports on the design and the technical evaluation of the performance of the sensing platform, tested on healthy subjects.

From the design to real e-textile platforms for Rehabilitation and chronic obstructive pulmonary diseases care.

In this paper is described the work done to move from the concept of a monitoring system based on a sensing textile platform to the working prototype, in the frame of two different European projects: INTERACTION and WELCOME.

Removing movement artifacts from equine ECG recordings acquired with textile electrodes.

This study reports on the implementation of a novel system to detect and reduce movement artifact (MA) contribution in electrocardiogram (ECG) recordings acquired from horses in free movement conditions. The system comprises both integrated textile electrodes for ECG acquisition and one triaxial accelerometer for movement monitoring. Here, ECG and physical activity are continuously acquired from seven horses through the wearable system and a model that integrates cardiovascular and movement information to estimate the MA contribution is implemented. Moreover, in this study we propose a new algorithm where the Stationary Wavelet Transform (SWT) decomposition algorithm is employed to identify and remove movement artifacts from ECG recodigns. Achieved results showed a reduction of MA percentage greater than 40% between before- and after- the application of the proposed algorithm to seven hours of recordings.

Exploiting wearable goniometer technology for motion sensing gloves.

This paper presents an innovative wearable kinesthetic glove realized with knitted piezoresistive fabric (KPF) sensor technology. The glove is conceived to capture hand movement and gesture by using KPF in a double-layer configuration working as angular sensors (electrogoniometers). The sensing glove prototype is endowed by three KPF goniometers, used to track flexion and extension movement of metacarpophalangeal joint of thumb, index, and middle fingers. The glove is devoted to the continuous monitoring of patients during their daily-life activities, in particular for stroke survivors during their rehabilitation. The prototype performances have been evaluated in comparison with an optical tracking system considered as a gold standard both for relieving static and dynamic posture and gesture of the hand. The introduced prototype has shown very interesting figures of merit. The angular error, evaluated through the standard Bland Altman analysis, has been estimated in ±3° which is slightly less accurate than commercial electrogoniometers. Moreover, a new conceptual prototype design, preliminary evaluated within this study, is presented and discussed in order to solve actual limitations in terms of number and type of sensor connections, avoiding mechanical constraints given by metallic inextensible wires and improving user comfort.

Advanced technology meets mental health: how smartphones, textile electronics, and signal processing can serve mental health monitoring, diagnosis, and treatment.

Mental disorders, characterized by impaired emotional and mood balance, are common in the West. Recent surveys have found that millions of people (age 18?65) have experienced some kind of mental disorder, such as psychotic disorder, major depression, bipolar disorder, panic disorder, social phobia, and somatoform disorder [1]. Specifically, in 2010, 164.8 million people in Europe were affected by such illnesses [1].

New generation of wearable goniometers for motion capture systems.

BACKGROUND: Monitoring joint angles through wearable systems enables human posture and gesture to be reconstructed as a support for physical rehabilitation both in clinics and at the patient's home. A new generation of wearable goniometers based on knitted piezoresistive fabric (KPF) technology is presented. METHODS: KPF single-and double-layer devices were designed and characterized under stretching and bending to work as strain sensors and goniometers. The theoretical working principle and the derived electromechanical model, previously proved for carbon elastomer sensors, were generalized to KPF. The devices were used to correlate angles and piezoresistive fabric behaviour, to highlight the differences in terms of performance between the single layer and the double layer sensors. A fast calibration procedure is also proposed. RESULTS: The proposed device was tested both in static and dynamic conditions in comparison with standard electrogoniometers and inertial measurement units respectively. KPF goniometer capabilities in angle detection were experimentally proved and a discussion of the device measurement errors of is provided. The paper concludes with an analysis of sensor accuracy and hysteresis reduction in particular configurations. CONCLUSIONS: Double layer KPF goniometers showed a promising performance in terms of angle measurements both in quasi-static and dynamic working mode for velocities typical of human movement. A further approach consisting of a combination of multiple sensors to increase accuracy via sensor fusion technique has been presented.

Wearable monitoring for mood recognition in bipolar disorder based on history-dependent long-term heart rate variability analysis.

Current clinical practice in diagnosing patients affected by psychiatric disorders such as bipolar disorder is based only on verbal interviews and scores from specific questionnaires, and no reliable and objective psycho-physiological markers are taken into account. In this paper, we propose to use a wearable system based on a comfortable t-shirt with integrated fabric electrodes and sensors able to acquire electrocardiogram, respirogram, and body posture information in order to detect a pattern of objective physiological parameters to support diagnosis. Moreover, we implemented a novel ad hoc methodology of advanced biosignal processing able to effectively recognize four possible clinical mood states in bipolar patients (i.e., depression, mixed state, hypomania, and euthymia) continuously monitored up to 18 h, using heart rate variability information exclusively. Mood assessment is intended as an intrasubject evaluation in which the patient's states are modeled as a Markov chain, i.e., in the time domain, each mood state refers to the previous one. As validation, eight bipolar patients were monitored collecting and analyzing more than 400 h of autonomic and cardiovascular activity. Experimental results demonstrate that our novel concept of personalized and pervasive monitoring constitutes a viable and robust clinical decision support system for bipolar disorders recognizing mood states with a total classification accuracy up to 95.81%.

Assessment of sensing fire fighters uniforms for physiological parameter measurement in harsh environment.

In the last few years, much effort has been devoted to the development of wearable sensing systems able to monitor physiological, behavioral, and environmental parameters. Less has been done on the accurate testing and assessment of this instrumentation, especially when considering devices thought to be used in harsh environments by subjects or operators performing intense physical activities. This paper presents methodology and results of the evaluation of wearable physiological sensors under these conditions. The methodology has been applied to a specific textile-based prototype, aimed at the real-time monitoring of rescuers in emergency contexts, which has been developed within a European funded project called ProeTEX. Wearable sensor measurements have been compared with the ones of suitable gold standards through Bland-Altman statistical analysis; tests were realized in controlled environments simulating typical intervention conditions, with temperatures ranging from 20 °C to 45 °C and subjects performing mild to very intense activities. This evaluation methodology demonstrated to be effective for the definition of the limits of use of wearable sensors. Furthermore, the ProeTEX prototype demonstrated to be reliable, since it produced negligible errors when used for up to 1 h in normal environmental temperature (20 °C and 35 °C) and up to 30 min in harsher environment (45 °C).

E-Textile platforms for rehabilitation.

This paper focus on SFIT platforms for rehabilitations and FES therapy. Two systems will be described, one developed to support patients during motor therapy, when they are still hospitalized, and after discharge, at home; the other is a sleeve integrating multi-electrodes patches, designed to allow FES therapy and EMG acquisition for patients affected by tremor. These examples prove that it is possible to combine fabric electrodes and biomechanical textile sensors to conceive systems where gesture recognition function can be combined with EMG detection and FES capability. These platforms can be easily used at home for daily therapy, as well as for telemedicine services.

BIOTEX--biosensing textiles for personalised healthcare management.

Textile-based sensors offer an unobtrusive method of continually monitoring physiological parameters during daily activities. Chemical analysis of body fluids, noninvasively, is a novel and exciting area of personalized wearable healthcare systems. BIOTEX was an EU-funded project that aimed to develop textile sensors to measure physiological parameters and the chemical composition of body fluids, with a particular interest in sweat. A wearable sensing system has been developed that integrates a textile-based fluid handling system for sample collection and transport with a number of sensors including sodium, conductivity, and pH sensors. Sensors for sweat rate, ECG, respiration, and blood oxygenation were also developed. For the first time, it has been possible to monitor a number of physiological parameters together with sweat composition in real time. This has been carried out via a network of wearable sensors distributed around the body of a subject user. This has huge implications for the field of sports and human performance and opens a whole new field of research in the clinical setting.

Comparative evaluation of susceptibility to motion artifact in different wearable systems for monitoring respiratory rate.

The purpose of this study is to comparatively evaluate the performance of different wearable systems based on indirect breathing monitoring in terms of susceptibility to motion artifacts. These performances are compared with direct respiratory measurements using a spirometer, which is accurate, reliable, and less sensitive to movement artifacts, but cannot be integrated into truly wearable form. Experiments were carried out on four indirect methods implemented into wearable systems, inductive plethysmography, impedance plethysmography, piezoresistive pneumography, and piezoelectric pneumography, to ascertain the performance of each of them in terms of noise due to movement artifacts, as well as to study the effects of different movements or gestures during each test. A group of volunteers was asked to wear all of the breath monitoring systems simultaneously along with the face mask of the spirometer while carrying out four physical exercises in a gym under controlled conditions. Data are analyzed in the time and frequency domain to estimate the frequency respiration from each wearable system and compare it with those of the spirometer. Results confirmed that all the wearable systems are somehow affected by movement artifacts, but statistical investigation showed that for most of the physical exercises, three out of four, piezoelectric pneumography provided best performance in terms of robustness and reduced susceptibility to movement artifacts.

Advances in textile sensing and actuation for e-textile applications.

SMART fabrics and interactive textiles (SFIT) are conceived as innovative textile structure integrating sensing, actuation, electronic, and power and/or communication functions. Due to their multifunctional interactivity, enabled by wearable devices that are flexible and conformable to the human body, e-textiles are considered relevant promoters of a higher quality of life and progress in biomedicine, as well as in several health-focused disciplines, such as biomonitoring, rehabilitation, telemedicine, teleassistance, ergonomics and sport medicine.

Smart garments for safety improvement of emergency/disaster operators.

The main purpose of the European project ProeTEX is to develop equipment to improve safety, coordination and efficiency of emergency disaster intervention personnel like fire-fighters or civil protection rescuers. The equipment consists of a new generation of "smart" garments, integrating wearable sensors which will allow monitoring physiological parameters, position and activity of the user, as like as environmental variables of the operating field in which rescuers are working: both commercial and newly developed textile and fibre based sensors will be included. The garments will also contain an electronic box to process data collected by the sensors and a communication system enabling the transmission of data to the other rescuers and to a monitoring station. Also a "smart" victim patch will be developed: a wearable garment which will allow monitoring physiological parameters of injured civilians involved in disasters, with the aim of optimizing their survival management.

Advances in textile technologies for unobtrusive monitoring of vital parameters and movements.

Recent research and development activity is described in the field of textile-based wearable systems for personalized health care. Sensorized shirts for vital signs monitoring and wearable systems for gesture and posture recognition are specifically illustrated, resulting from the EU funded project my heart.

Wearable healthcare systems, new frontiers of e-textile.

There is a growing need of renovation in our health care managing systems; people need to be more interactive and more conscious of their own health condition in a way to adjust incorrect lifestyles, to obtain a personalized therapy tuned to their own physiological reactions and on their own environmental condition. To gain knowledge of a citizen's health status and to monitor without harassing them (until they refuse any medical supervision), a comfortable remote monitoring of important physiological parameters is necessary. The approach is therefore to integrate system solutions into functional clothes with integrated textile sensors. The combination of functional clothes and integrated electronics and on-body processing, is defined as e-textile and gives rise to intelligent biomedical clothes. Systems, designed to be minimally invasive, are based on smart textile technologies, where conductive and piezoresistive materials in the form of fiber and yarn are used to realize clothes, in which knitted fabric sensors and electrodes are distributed and connected to an electronic portable unit. These systems are able to detect, acquire and transmit physiological signals. They are conformable to the human body, and move towards improving the patient's quality of life and their autonomy. These systems are also cost-effective in providing around-the-clock assistance, in helping physicians to monitor for example cardiac patients during periods of rehabilitation, and in addition result in decreased hospitalization time. Finally, by providing direct feedback to the users, they improve their awareness and potentially allow better control of their own condition, while the simultaneous recording of vital signs permits parameter extrapolation and inter-signal elaboration that contributes to produce alert messages and personalized synoptic tables of the patient's health.

A wearable health care system based on knitted integrated sensors.

A comfortable health monitoring system named WEALTHY is presented. The system is based on a textile wearable interface implemented by integrating sensors, electrodes, and connections in fabric form, advanced signal processing techniques, and modern telecommunication systems. Sensors, electrodes and connections are realized with conductive and piezoresistive yarns. The sensorized knitted fabric is produced in a one step process. The purpose of this paper is to show the feasibility of a system based on fabric sensing elements. The capability of this system to acquire simultaneously several biomedical signals (i.e. electrocardiogram, respiration, activity) has been investigated and compared with a standard monitoring system. Furthermore, the paper presents two different methodologies for the acquisition of the respiratory signal with textile sensors. Results show that the information contained in the signals obtained by the integrated systems is comparable with that obtained by standard sensors. The proposed system is designed to monitor individuals affected by cardiovascular diseases, in particular during the rehabilitation phase. The system can also help professional workers who are subject to considerable physical and psychological stress and/or environmental and professional health risks.