Analysis of Signal Processing Methods to Reject the DC Offset Contribution of Static Reflectors in FMCW Radar-Based Vital Signs Monitoring.

Frequency-modulated continuous wave (FMCW) radars are currently being investigated for remote vital signs monitoring (measure of respiration and heart rates) as an innovative wireless solution for healthcare and ambient assisted living. However, static reflectors (furniture, objects, stationary body parts, etc.) within the range or range angular bin where the subject is present contribute in the Doppler signal to a direct current (DC) offset. The latter is added to the person's information, containing also a useful DC component, causing signal distortion and hence reducing the accuracy in measuring the vital sign parameters. Removing the sole contribution of the unwanted DC offset is fundamental to perform proper phase demodulation, so that accurate vital signs monitoring can be achieved. In this work, we analyzed different DC offset calibration methods to determine which one achieves the highest accuracy in measuring the physiological parameters as the transmitting frequency varies. More precisely, by using two FMCW radars, operating below 10 GHz and at millimeter wave (mmWave), we applied four DC offset calibration methods to the baseband radar signals originated by the cardiopulmonary activities. We experimentally determined the accuracy of the methods by measuring the respiration and the heart rates of different subjects in an office setting. It was found that the linear demodulation outperforms the other methods if operating below 10 GHz while the geometric fitting provides the best results at mmWave.

Automatic radar-based 2-D localization exploiting vital signs signatures.

In light of the continuously and rapidly growing senior and geriatric population, the research of new technologies enabling long-term remote patient monitoring plays an important role. For this purpose, we propose a single-input-multiple-output (SIMO) frequency-modulated continuous wave (FMCW) radar system and a signal processing technique to automatically detect the number and the 2-D position (azimuth and range information) of stationary people (seated/lying down). This is achieved by extracting the vital signs signatures of each single individual, separating the Doppler shifts caused by the cardiopulmonary activities from the unwanted reflected signals from static reflectors and multipaths. We then determine the number of human subjects present in the monitored environment by counting the number of extracted vital signs signatures while the 2-D localization is performed by measuring the distance from the radar where the vital signs information is sensed (i.e., locating the thoracic region). We reported maximum mean absolute errors (MAEs) of 0.1 m and 2.29[Formula: see text] and maximum root-mean-square errors (RMSEs) of 0.12 m and 3.04[Formula: see text] in measuring respectively the ranges and azimuth angles. The experimental validation demonstrated the ability of the proposed approach in monitoring paired human subjects in a typical office environment.

Capacitively-Coupled ECG and Respiration for Sleep-Wake Prediction and Risk Detection in Sleep Apnea Patients.

Obstructive sleep apnea (OSA) patients would strongly benefit from comfortable home diagnosis, during which detection of wakefulness is essential. Therefore, capacitively-coupled electrocardiogram (ccECG) and bioimpedance (ccBioZ) sensors were used to record the sleep of suspected OSA patients, in parallel with polysomnography (PSG). The three objectives were quality assessment of the unobtrusive signals during sleep, prediction of sleep-wake using ccECG and ccBioZ, and detection of high-risk OSA patients. First, signal quality indicators (SQIs) determined the data coverage of ccECG and ccBioZ. Then, a multimodal convolutional neural network (CNN) for sleep-wake prediction was tested on these preprocessed ccECG and ccBioZ data. Finally, two indices derived from this prediction detected patients at risk. The data included 187 PSG recordings of suspected OSA patients, 36 (dataset "Test") of which were recorded simultaneously with PSG, ccECG, and ccBioZ. As a result, two improvements were made compared to prior studies. First, the ccBioZ signal coverage increased significantly due to adaptation of the acquisition system. Secondly, the utility of the sleep-wake classifier increased as it became a unimodal network only requiring respiratory input. This was achieved by using data augmentation during training. Sleep-wake prediction on "Test" using PSG respiration resulted in a Cohen's kappa (κ) of 0.39 and using ccBioZ in κ = 0.23. The OSA risk model identified severe OSA patients with a κ of 0.61 for PSG respiration and κ of 0.39 using ccBioZ (accuracy of 80.6% and 69.4%, respectively). This study is one of the first to perform sleep-wake staging on capacitively-coupled respiratory signals in suspected OSA patients and to detect high risk OSA patients based on ccBioZ. The technology and the proposed framework could be applied in multi-night follow-up of OSA patients.

Enabling Robust Radar-Based Localization and Vital Signs Monitoring in Multipath Propagation Environments.

OBJECTIVE: Over the last two decades, radar-based contactless monitoring of vital signs (heartbeat and respiration rate) has raised increasing interest as an emerging and added value to health care. However, until now, the flaws caused by indoor multipath propagation formed a fundamental hurdle for the adoption of such technology in practical healthcare applications where reliability and robustness are crucial. Multipath reflections, originated from one person, combine with the direct signals and multipaths of other people and stationary objects, thus jeopardizing individual vital signs extraction and localization. This work focuses on tackling indoor multipath propagation. METHODS: We describe a methodology, based on accurate models of the indoor multipaths and of the radar signals, that enables separating the undesired multipaths from desired signals of multiple individuals, removing a key obstacle to real-world contactless vital signs monitoring and localization. RESULTS: We also demonstrated it by accurately measure individual heart rates, respiration rates, and absolute distances (range information) of paired volunteers in a challenging real-world office setting. CONCLUSION: The approach, validated using a frequency-modulated continuous wave (FMCW) radar, was shown to function in an indoor environment where radar signals are severely affected by multipath reflections. SIGNIFICANCE: Practical applications arise for health care, assisted living, geriatric and quarantine medicine, rescue and security purposes.

Capacitively-coupled ECG and respiration for the unobtrusive detection of sleep apnea.

OBJECTIVE: The performance of a novel unobtrusive system based on capacitively-coupled electrocardiography (ccECG) combined with different respiratory measurements is evaluated for the detection of sleep apnea. APPROACH: A sleep apnea detection algorithm is proposed, which can be applied to electrocardiography (ECG) and ccECG, combined with different unobtrusive respiratory measurements, including ECG derived respiration (EDR), respiratory effort measured using the thoracic belt (TB) and capacitively-coupled bioimpedance (ccBioz). Several ECG, respiratory and cardiorespiratory features were defined, of which the most relevant ones were identified using a random forest based backwards wrapper. Using this relevant feature set, a least-squares support vector machine classifier was trained to decide if a one minute segment is apneic or not, based on the annotated polysomnography (PSG) data of 218 patients suspected of having sleep apnea. The obtained classifier was then tested on the PSG and capacitively-coupled data of 28 different patients. MAIN RESULTS: On the PSG data, an AUC of 76.3% was obtained when the ECG was combined with the EDR. Replacing the EDR with the TB led to an AUC of 80.0%. Using the ccECG and ccBioz or the ccECG and TB resulted in similar performances as on the PSG data, while using the ccECG and ccECG-based EDR resulted in a drop in AUC to 67.4%. SIGNIFICANCE: This is the first study which tests an apnea detection algorithm on capacitively-coupled ECG and bioimpedance signals and shows promising results on the capacitively-coupled data set. However, it was shown that the EDR could not be accurately estimated from the ccECG signals. Further research into the effect that respiration has on the ccECG is needed to propose alternative EDR estimates.

A 400 GΩ Input-Impedance Active Electrode for Non-Contact Capacitively Coupled ECG Acquisition With Large Linear-Input-Range and High CM-Interference-Tolerance.

Electrocardiogram (ECG) is one of the major physiological vital signs and an effective monitoring method for patients with cardiovascular diseases. However, existing ECG recordings require a galvanic body contact, which is unpractical in daily life. This paper presents the design of an ECG chip that facilitates non-contact ECG recording through capacitive coupling. With the input impedance boosting techniques, as well as an active driven-right-leg (DRL) which boosts common-mode rejection ratio to 70 dB, the single-ended capacitive feedback active electrode (AE) achieves ultra-high input impedance of 400 GΩ (< 0.5 Hz), a large common-mode interference tolerance (2.8 VPP), and a high linear-input-range (220 m VPP). Implemented in 0.18 µm 5V CMOS process, the prototype occupies an area of 1.23 mm2, and consumes 18 µA and 13 µA for the AE and DRL, respectively. Real life non-contact capacitively coupled ECG acquisition has been demonstrated, obtaining ECG waves and heart rate in the presence of motion artifacts as well as ambient interference.

Capacitive multi-electrode array with real-time electrode selection for unobtrusive ECG & BIOZ monitoring.

Capacitively-coupled ECG (ccECG) and bioimpedance (ccBIOZ) measurements are highly sensitive to motion artefacts. This limits their use in real-life situations. This work presents an array-based system for the simultaneous acquisition of ccECG and ccBIOZ, together with a quality-based electrode scanning approach for ccECG. This allows to increase the time coverage of contactless measurements in real-life situations and reduces the impact of artefacts. This solution was evaluated on a car seat and a mattress prototype. Results show the benefit of this combined array and algorithm approach: for every body position the algorithm was able to find more than one electrode combination providing high-quality ccECG. Night-long recordings were also performed, resulting in a mean time coverage of 72.5%.

A Direct Phase-Tracking Doppler Radar Using Wavelet Independent Component Analysis for Non-Contact Respiratory and Heart Rate Monitoring.

A continuous wave Doppler radar, operating as a phase-locked-loop in phase demodulator configuration, is proposed and in vivo demonstrated for noncontact vital signs monitoring. The radar architecture exhibits a unique precision in tracking the phase modulation caused by human cardiopulmonary activity from which heartbeat and respiration can simultaneously be extracted. The single mixer architecture is immune to the null point and does not require small-angle approximation conditions, which distinguishes it from pre-existing other approaches. This enables the proposed radar to behave highly linear, with very precise detection of phase modulations induced by any kind of movement, independently from amplitude and speed. After simulations and technical tests to validate functionality and safety of the proposed architecture, a practical setup was demonstrated on human volunteers. Wavelet independent component analysis was applied to successfully retrieve respiratory and heart rate information from the radar baseband signal.

Evaluation of a Multichannel Non-Contact ECG System and Signal Quality Algorithms for Sleep Apnea Detection and Monitoring.

Sleep-related conditions require high-cost and low-comfort diagnosis at the hospital during one night or longer. To overcome this situation, this work aims to evaluate an unobtrusive monitoring technique for sleep apnea. This paper presents, for the first time, the evaluation of contactless capacitively-coupled electrocardiography (ccECG) signals for the extraction of sleep apnea features, together with a comparison of different signal quality indicators. A multichannel ccECG system is used to collect signals from 15 subjects in a sleep environment from different positions. Reference quality labels were assigned for every 30-s segment. Quality indicators were calculated, and their signal classification performance was evaluated. Features for the detection of sleep apnea were extracted from capacitive and reference signals. Sleep apnea features related to heart rate and heart rate variability achieved high similarity to the reference values, with p-values of 0.94 and 0.98, which is in line with the more than 95% beat-matching obtained. Features related to signal morphology presented lower similarity with the reference, although signal similarity metrics of correlation and coherence were relatively high. Quality-based automatic classification of the signals had a maximum accuracy of 91%. Best-performing quality indicators were based on template correlation and beat-detection. Results suggest that using unobtrusive cardiac signals for the automatic detection of sleep apnea can achieve similar performance as contact signals, and indicates clinical value of ccECG. Moreover, signal segments can automatically be classified by the proposed quality metrics as a pre-processing step. Including contactless respiration signals is likely to improve the performance and provide a complete unobtrusive cardiorespiratory monitoring solution; this is a promising alternative that will allow the screening of more patients with higher comfort, for a longer time, and at a reduced cost.

Systolic Time Interval Estimation Using Continuous Wave Radar With On-Body Antennas.

The estimation of systolic time intervals (STIs) is done using continuous wave (CW) radar at 2.45 GHz with an on-body antenna. MOTIVATION: In the state of the art, typically bioimpedance, heart sounds and/or ultrasound are used to measure STIs. All three methods suffer from insufficient accuracy of STI estimation due to various reasons. CW radar is investigated for its ability to overcome the deficiencies in the state of the art. METHODS: Ten healthy male subjects aged 25-45 were asked to lie down at a 30 incline. Recordings of 60 s were taken without breathing and with paced breathing. Heart sounds, electrocardiogram, respiration, and impedance cardiogram were measured simultaneously as reference. The radar antennas were placed at two positions on the chest. The antennas were placed directly on the body as well as with cotton textile in between. The beat to beat STIs have been determined from the reference signals as well as CW radar signals. RESULTS: The results indicate that CW radar can be used to estimate STIs in ambulatory monitoring. SIGNIFICANCE: The results pave way to a potentially more compact method of estimating STIs, which can be integrated into a wearable device.

Frequency-Tracking CW Doppler Radar Solving Small-Angle Approximation and Null Point Issues in Non-Contact Vital Signs Monitoring.

A Doppler radar operating as a Phase-Locked-Loop (PLL) in frequency demodulator configuration is presented and discussed. The proposed radar presents a unique architecture, using a single channel mixer, and allows to detect contactless vital signs parameters while solving the null point issue and without requiring the small angle approximation condition. Spectral analysis, simulations, and experimental results are presented and detailed to demonstrate the feasibility and the operational principle of the proposed radar architecture.

Noncontact ECG recording system with real time capacitance measurement for motion artifact reduction.

A system for noncontact ECG recording is proposed that measures the real time electrode-body capacitance concurrently with the ECG as a reference signal for motion artifact reduction. Simultaneous recordings of these two signals from the human body in the presence of electrode motion artifacts are shown and an adaptive least-mean-squares (LMS) filtering algorithm run on these signals is demonstrated to be able to reduce the severity of certain types of electrode motion artifacts.

Clinical validation of a low-power and wearable ECG patch for long term full-disclosure monitoring.

BACKGROUND: Detection of intermittent atrial fibrillation (AF) is done using a 24-h Holter. Holter recordings are powerful but lack the comfort and have limited recording times resulting in under diagnosing of intermittent AF. OBJECTIVE: Within this work we evaluated and compared a novel miniaturized three-channel ECG monitoring patch versus a 24-h Holter system. METHODS: Both patients with a chronic AF rhythm (n=5) as well as patients with an AF rhythm that underwent electrical reconversion (n = 5) were equipped with both a 24-h Holter and ECG patch. RESULTS: Alignment of raw data of both ECG systems allowed cross-correlation analysis. Overall good correlations of up to 85% were obtained. RR-interval analysis of both systems resulted in very high correlations of 99% and higher. AF analysis showed correct identification of AF on both ECG systems. CONCLUSIONS: The performance of our ECG patch matches that of the 24-h Holter and could provide a suitable tool for long-term monitoring applications.

In vivo validation of the electronic depth control probes.

In this article, we evaluated the electrophysiological performance of a novel, high-complexity silicon probe array. This brain-implantable probe implements a dynamically reconfigurable voltage-recording device, coordinating large numbers of electronically switchable recording sites, referred to as electronic depth control (EDC). Our results show the potential of the EDC devices to record good-quality local field potentials, and single- and multiple-unit activities in cortical regions during pharmacologically induced cortical slow wave activity in an animal model.

Ultra-Thin Chip Package (UTCP) and stretchable circuit technologies for wearable ECG system.

A comfortable, wearable wireless ECG monitoring system is proposed. The device is realized using the combination of two proprietary advanced technologies for electronic packaging and interconnection : the UTCP (Ultra-Thin Chip Package) technology and the SMI (Stretchable Mould Interconnect) technology for elastic and stretchable circuits. Introduction of these technologies results in small fully functional devices, exhibiting a significant increase in user comfort compared to devices fabricated with more conventional packaging and interconnection technologies.

A low-power, wireless, 8-channel EEG monitoring headset.

Micro- and nano-technology has enabled development of smaller and smarter wearable devices for medical and lifestyle related applications. In particular, recent advances in EEG monitoring technologies pave the way for wearable, wireless EEG monitoring devices. Here, a low-power wireless EEG sensor platform that measures 8-channels of EEG, is described. The platform is integrated into a wearable headset for ambulatory monitoring of EEG. While using standard EEG electrodes without conductive gel, a first evaluation shows the wireless headset is comparable to the reference system when looking at alpha wave discrimination. This device combines low-noise, and low-power functionality into an easy-to-use wireless headset, providing a first step towards a fully integrated, fully functional wearable wireless EEG monitoring system.

Control and data acquisition software for high-density CMOS-based microprobe arrays implementing electronic depth control.

This paper presents the NeuroSelect software for managing the electronic depth control of cerebral CMOS-based microprobes for extracellular in vivo recordings. These microprobes contain up to 500 electronically switchable electrodes which can be appropriately selected with regard to specific neuron locations in the course of a recording experiment. NeuroSelect makes it possible to scan the electrodes electronically and to (re)select those electrodes of best signal quality resulting in a closed-loop design of a neural acquisition system. The signal quality is calculated by the relative power of the spikes compared with the background noise. The spikes are detected by an adaptive threshold using a robust estimator of the standard deviation. Electrodes can be selected in a manual or semi-automatic mode based on the signal quality. This electronic depth control constitutes a significant improvement for multielectrode probes, given that so far the only alternative has been the fine positioning by mechanical probe translation. In addition to managing communication with the hardware controller of the probe array, the software also controls acquisition, processing, display and storage of the neural signals for further analysis.

An integrated circuit for wireless ambulatory arrhythmia monitoring systems.

An ECG signal processor (ESP) is proposed for the low energy wireless ambulatory arrhythmia monitoring system. The ECG processor mainly performs filtering, compression, classification and encryption. The data compression flow consisting of skeleton and modified Huffman coding is the essential function to reduce the transmission energy consumption and the memory capacity, which are the most energy consuming part. The classification flow performs the arrhythmia analysis to alert the abnormality. The proposed ESP IC is implemented in 0.18-microm CMOS process and integrated into the wireless arrhythmia monitoring sensor platform. By integration of the ESP, the total system energy reduction is evaluated by 95.6%.

The NeuroProbes project: a concept for electronic depth control.

The European project NeuroProbes has introduced a new methodology to allow the fine positioning of electrodes within an implantable probe with respect to individual neurons. In this approach, probes are built with a very large number of electrodes which are electronically selectable. This feature is implemented thanks to the modular approach adopted in NeuroProbes, which will allow the implementation of integrated electronics both along the probe shaft and on the array backbone.