Comparison of baseline correction algorithms for in vivo 1H-MRS.

Proton MRS is used clinically to collect localized, quantitative metabolic data from living tissues. However, the presence of baselines in the spectra complicates accurate MRS data quantification. The occurrence of baselines is not specific to short-echo-time MRS data. In short-echo-time MRS, the baseline consists typically of a dominating macromolecular (MM) part, and can, depending on B0 shimming, poor voxel placement, and/or localization sequences, also contain broad water and lipid resonance components, indicated by broad components (BCs). In long-echo-time MRS, the MM part is usually much smaller, but BCs may still be present. The sum of MM and BCs is denoted by the baseline. Many algorithms have been proposed over the years to tackle these artefacts. A first approach is to identify the baseline itself in a preprocessing step, and a second approach is to model the baseline in the quantification of the MRS data themselves. This paper gives an overview of baseline handling algorithms and also proposes a new algorithm for baseline correction. A subset of suitable baseline removal algorithms were tested on in vivo MRSI data (semi-LASER at TE = 40 ms) and compared with the new algorithm. The baselines in all datasets were removed using the different methods and subsequently fitted using spectrIm-QMRS with a TDFDFit fitting model that contained only a metabolite basis set and lacked a baseline model. The same spectra were also fitted using a spectrIm-QMRS model that explicitly models the metabolites and the baseline of the spectrum. The quantification results of the latter quantification were regarded as ground truth. The fit quality number (FQN) was used to assess baseline removal effectiveness, and correlations between metabolite peak areas and ground truth models were also examined. The results show a competitive performance of our new proposed algorithm, underscoring its automatic approach and efficiency. Nevertheless, none of the tested baseline correction methods achieved FQNs as good as the ground truth model. All separately applied baseline correction methods introduce a bias in the observed metabolite peak areas. We conclude that all baseline correction methods tested, when applied as a separate preprocessing step, yield poorer FQNs and biased quantification results. While they may enhance visual display, they are not advisable for use before spectral fitting.

Simple Wireless Impedance Pneumography System for Unobtrusive Sensing of Respiration.

This extended paper presents the development and implementation at a prototype level of a wireless, low-cost system for the measurement of the electrical bioimpedance of the chest with two channels using the AD5933 in a bipolar electrode configuration to measure impedance pneumography. The measurement device works for impedance measurements ranging from 1 Ω to 1800 Ω. Fifteen volunteers were measured with the prototype. We found that the left hemithorax has higher impedance compared to the right hemithorax, and the acquired signal presents the phases of the respiratory cycle with variations between 1 Ω, in normal breathing, to 6 Ω in maximum inhalation events. The system can measure the respiratory cycle variations simultaneously in both hemithorax with a mean error of -0.18 ± 1.42 BPM (breaths per minute) in the right hemithorax and -0.52 ± 1.31 BPM for the left hemithorax, constituting a useful device for the breathing rate calculation and possible screening applications.

A brief tablet-based intervention benefits linguistic and communicative abilities in toddlers and preschoolers.

Young children's linguistic and communicative abilities are foundational for their academic achievement and overall well-being. We present the positive outcomes of a brief tablet-based intervention aimed at teaching toddlers and preschoolers new word-object and letter-sound associations. We conducted two experiments, one involving toddlers ( ~ 24 months old, n = 101) and the other with preschoolers ( ~ 42 months old, n = 152). Using a pre-post equivalent group design, we measured the children's improvements in language and communication skills resulting from the intervention. Our results showed that the intervention benefited toddlers' verbal communication and preschoolers' speech comprehension. Additionally, it encouraged vocalizations in preschoolers and enhanced long-term memory for the associations taught in the study for all participants. In summary, our study demonstrates that the use of a ludic tablet-based intervention for teaching new vocabulary and pre-reading skills can improve young children's linguistic and communicative abilities, which are essential for future development.

Multi-frequency Electrical Impedance Pneumography System as Point-Of-Care Device.

In this work we present the development of a multi-frequency electrical impedance pneumography (EIP) system based on a portable acquisition device and a mobile platform. This design is intended as an upgrade to our previous device for clinical use in the screening of patients with pulmonary diseases. The acquisition device uses the bioimpedance analog front end MAX30001, a mux/demux stage, Bluetooth 4.0 communication and an ESP32 microcontroller unit. It generates an excitation current of 8 µApp in a range of selectable frequencies from 1 kHz to 130 kHz. The mobile platform provides a real-time respiration signal at 64 S/s and allows the configuration of the device. Results show less error in higher frequencies, which are the most common in these applications, ensuring the feasibility of the system for use in humans. Some hardware constraints related to EIP integrated circuits are discussed, an their effect in the signal acquisition.

Carbamazepine Biosensor Development for Epilepsy Patient Screening.

The San Carlos population in Chile is an example of an underserved community due to lack of timely access to regular controls and laboratory results. One particular challenge is the adherence to treatment of Epilepsy patients. In this work, we present the design and proof-of-concept of a Point of Care Device (POCD) to measure carbamazepine levels in saliva to screen for correct dose prescription among epilepsy patients. We present the Screen Printed Electrode design and activating circuit and preliminary results to verify feasibility of the biosensor. Future steps include the fabrication of the device itself and validation with the target population.

Wireless Low-Cost Bioimpedance Measurement Device for Lung Capacity Screening.

This paper presents the development and implementation at a prototype level of a wireless, low-cost system for the measurement of the electrical bio-impedance of the chest with two channels using the AD5933 in a bipolar electrode configuration to measure lung volume variation. 15 volunteers were measured with the prototype, and the acquired signal presents the phases of the respiratory cycle, useful for the breathing rate calculation and for possible screening applications.

SMART--an integrated wireless system for monitoring unattended patients.

Monitoring vital signs and locations of certain classes of ambulatory patients can be useful in overcrowded emergency departments and at disaster scenes, both on-site and during transportation. To be useful, such monitoring needs to be portable and low cost, and have minimal adverse impact on emergency personnel, e.g., by not raising an excessive number of alarms. The SMART (Scalable Medical Alert Response Technology) system integrates wireless patient monitoring (ECG, SpO(2)), geo-positioning, signal processing, targeted alerting, and a wireless interface for caregivers. A prototype implementation of SMART was piloted in the waiting area of an emergency department and evaluated with 145 post-triage patients. System deployment aspects were also evaluated during a small-scale disaster-drill exercise.

Wearable EMG Shirt for Upper Limb Training.

This work presents a wearable shirt fitted with dry electrodes to measure EMG in upper limbs during physical exercise. The hardware acquires signals from 6 channels and transmits wirelessly to a PC via Bluetooth. In the PC, EMG signals are analyzed to give feedback to the user regarding the exercise being performed. To alert for muscle fatigue, the Dimitrov index is used, with much better results that classic mean or median EMG frequency tracking. The system is able to monitor EMG activity and provide valuable information in real-time for professional and amateur athletes and their sports coach, improving their training protocols.

Design of an intraoperative peritoneal lavage device.

This paper consists of the design and construction of an intraoperative peritoneal lavage device. It is intended for cleaning the intra-abdominal cavity during a surgical procedure, once the etiology of a peritonitis has been identified and treated. Its purpose is to improve the current standard treatment consisting of simple pouring saline solution. A good washing procedure aids stopping the inflammatory and infectious process generated after the contamination due to the perforation of a hollow viscera. COMSOL Multiphysics software was used to simulate the biomechanical behavior of the liver against localized pressure. A graphical interface allows the user to predict liver deformation under different fluid pressures and positions simulating the lavage procedure. A preliminary prototype was implemented and a clinical trial was approved in an animal model. Three intraperitoneal structures belonging to a sheep were analyzed to observe the effect of the lavage. In closing, the final prototype implemented delivers a maximum force of 0.08 [N] and a pressure of 25.6 [kPa], and complied with the specialist's expectations.

Noninvasive health condition monitoring device for workers at high altitudes conditions.

This work presents the design and implementation of a continuous monitoring device to control the health state of workers, for instance miners, at high altitudes. The extreme ambient conditions are harmful for peoples' health; therefore a continuous control of the workers' vital signs is necessary. The developed system includes physiological variables: electrocardiogram (ECG), respiratory activity and body temperature (BT), and ambient variables: ambient temperature (AT) and relative humidity (RH). The noninvasive sensors are incorporated in a t-shirt to deliver a functional device, and maximum comfort to the users. The device is able to continuously calculate heart rate (HR) and respiration rate (RR), and establish a wireless data transmission to a central monitoring station.

Non-invasive BCG monitoring for non-traditional settings.

This paper presents the results from actual measurements of cardiac activity acquired through the use of noninvasive sensors to detect Ballistocardiogram (BCG). The results show that it is feasible to unobtrusively monitor heart rate in non-standard settings such as waiting rooms or at school using simple chairs fitted with capacitive sensors. The selected sensors, based on electromechanical principles, are able to measure BCG from a variety of subjects. We present the results for 114 participants from homes, school and a hospital waiting room, adding up over 815 minutes of data.

Myoelectric intuitive control and transcutaneous electrical stimulation of the forearm for vibrotactile sensation feedback applied to a 3D printed prosthetic hand.

This paper presents the development of a myoelectric prosthetic hand based on a 3D printed model. A myoelectric control strategy based on artificial neural networks is implemented on a microcontroller for online position estimation. Position estimation performance achieves a correlation index of 0.78. Also a study involving transcutaneous electrical stimulation was performed to provide tactile feedback. A series of stimulations with controlled parameters were tested on five able-body subjects. A single channel stimulator was used, positioning the electrodes 8 cm on the wrist over the ulnar and median nerve. Controlling stimulation parameters such as intensity, frequency and pulse width, the subjects were capable of distinguishing different sensations over the palm of the hand. Three main sensations where achieved: tickling, pressure and pain. Tickling and pressure were discretized into low, moderate and high according to the magnitude of the feeling. The parameters at which each sensation was obtained are further discussed in this paper.

Noninvasive ambulatory measurement system of cardiac activity.

This work implements a noninvasive system that measures the movements caused by cardiac activity. It uses unobtrusive Electro-Mechanical Films (EMFi) on the seat and on the backrest of a regular chair. The system detects ballistocardiogram (BCG) and respiration movements. Real data was obtained from 54 volunteers. 19 of them were measured in the laboratory and 35 in a hospital waiting room. Using a BIOPAC acquisition system, the ECG was measured simultaneously to the BCG for comparison. Wavelet Transform (WT) is a better option than Empirical Mode Decomposition (EMD) for signal extraction and produces higher effective measurement time. In the laboratory, the best results are obtained on the seat. The correlation index was 0.9800 and the Bland-Altman limits of agreement were 0.7136 ± 4.3673 [BPM]. In the hospital waiting room, the best results are also from the seat sensor. The correlation index was 0.9840, and the limits of agreement were 0.4386 ± 3.5884 [BPM]. The system is able to measure BCG in an unobtrusive way and determine the cardiac frequency with high precision. It is simple to use, which means the system can easily be used in non-standard settings: resting in a chair or couch, at the gym, schools or in a hospital waiting room, as shown.

Validation of non-invasive monitoring device to evaluate sleep quality.

This paper presents the validation of a noninvasive sleep monitoring device and sleep quality evaluation. The system is based on an array of pressure sensors positioned on the bed that can measure relevant parameters to estimate sleep quality. This device can measure time in bed (TB), body movements (BM), the thorax expansion, periods out of bed (POB) and apnea events. We compare the results of the unobtrusive pressure sensor array with traditional polysomnography (PSG). The algorithms developed for the device provide a very good detection of all the parameters required to estimate sleep quality as compared to the gold-standard data for a study of 30 patients. For the periods out of bed it presents a sensibility (Se) and specificity (Sp) of 100%. To grade the severity of sleep apnea we compare the number of events per hour or apnea-hypopnea index (AHI) obtained by the device and the PSG; obtaining a Se of 94% and a Sp of 61%. These results validate the use of the device for screening of sleep apnea disease.

Eye-tracking capabilities of low-cost EOG system.

This paper presents the design and implementation of a low-cost eye tracking system that allows measuring the rotational angle of the eye and gaze direction in healthy individuals. The system consists of an EOG circuit with simple components that acquire both horizontal and vertical eye movement through regular all-purpose contact electrodes. Then the data are analyzed and translated into corresponding angle values representing the eye rotation angle in both orientations. Results show that horizontal angle measurements are much more accurate than vertical measurements. A discussion regarding the performance and possible improvements is presented.

Identifying and extracting patient smoking status information from clinical narrative texts in Spanish.

In this work we present a system to identify and extract patient's smoking status from clinical narrative text in Spanish. The clinical narrative text was processed using natural language processing techniques, and annotated by four people with a biomedical background. The dataset used for classification had 2,465 documents, each one annotated with one of the four smoking status categories. We used two feature representations: single word token and bigrams. The classification problem was divided in two levels. First recognizing between smoker (S) and non-smoker (NS); second recognizing between current smoker (CS) and past smoker (PS). For each feature representation and classification level, we used two classifiers: Support Vector Machines (SVM) and Bayesian Networks (BN). We split our dataset as follows: a training set containing 66% of the available documents that was used to build classifiers and a test set containing the remaining 34% of the documents that was used to test and evaluate the model. Our results show that SVM together with the bigram representation performed better in both classification levels. For S vs NS classification level performance measures were: ACC=85%, Precision=85%, and Recall=90%. For CS vs PS classification level performance measures were: ACC=87%, Precision=91%, and Recall=94%.

Monitoring technology for wheelchair users with advanced multiple sclerosis.

This paper presents a non-invasive assistive device for people with advanced Multiple Sclerosis (MS) who use electric power wheelchairs (EPW). The proposed system can acquire respiration and heart activity from ballistocardiogram (BCG), seat and back pressure distribution, wheelchair tilt angle and ambient temperature and relative humidity. The sensors collect information related to the main issues of MS patients: fatigue, heat sensitivity and low mobility. Preliminary results show the signals as the wheelchair is moving, stopped and tilting. The system is able to capture sufficient relevant information to provide suggestions and alarms in a future stage. The system will be tested at The Boston Home, a specialized residence for adults with advanced MS.

Clustering of atrial fibrillation based on surface ECG measurements.

Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical research. In particular, the study of AF types or sub-classes is a very interesting research topic. In this paper we present a preliminary study to find sub-classes of AF from real 12-lead ECG recordings using k-means and hierarchical clustering algorithms. We applied blind source separation to an initial set of 218 recordings from which we extracted a subset of 136 atrial activity signals displaying known properties of AF. As features for clustering we proposed the peak frequency mean value (PFM), peak frequency standard deviation (PFSD) and the spectral concentration (SC). We computed the silhouette coefficient to obtain an optimal number of clusters of k=5, and conducted preliminary feature selection to evaluate clustering quality. We observed that the separability increases if we discard SC as a feature. The proposed method is the first stage to a future AF classification method, which combined with specialist advice, should help in the clinical field.

Atrial activity selection for atrial fibrillation ECG recordings.

In this paper we apply independent component analysis (ICA) followed by second order blind identification (SOBI) to an atrial fibrillation (AF) 12-lead electrocardiogram (ECG) recording in order to extract the source that represents atrial activity (AA) (ICA-SOBI method). Still, there is no assurance that only one source obtained from this method will contain AA, and thus we aim to select the most representative source of AA. The novelty in this paper is the proposal of three parameters to select the most representative source of AA. These parameters are correlation coefficient with lead V1 (CV1), peak factor (PF) and spectral concentration (SC). The first two parameters are introduced as new indicators, addressing features overlooked by the SC even when they are present in AA during AF. For synthesized data, at least two of the three parameters select the same representation of AA in 93.3% of the cases. For real data (218 ECG recordings), we observe that PF presents, in 89.5% of the cases, values between 2 and 4.5 for the selected sources, ensuring a well-defined range of values for AA. The actual values of CV1 and SC were scattered throughout their possible ranges (0-1 for CV1 and 0.08-0.7 for SC), and the correlation coefficient between these variables was found to be ρ=0.58. We compared our results with three known algorithms: QRST cancellation, principal components analysis (PCA) and ICA-SOBI. The results obtained from this comparison show that our proposed methods to select the best representation of AA in general outperform the three above-mentioned algorithms.