Niemanndickinson0818

This paper introduces a low-cost phantom system that simulates fetal movements (FMVs) for the first time. This vibration system can be used for testing wearable inertial sensors which detect FMVs from the abdominal wall. The system consists of a phantom abdomen, a linear stage with a stepper motor, a tactile transducer, and control circuits. The linear stage is used to generate mechanical vibrations which are transferred to the latex abdomen. A tactile transducer is implemented to add environmental noise to the system. The system is characterized and tested using a wireless sensor. The sensor recordings are analyzed using time-frequency analysis and the results are compared to real FMVs reported in the literature. Experiments are conducted to characterize the vibration range, frequency response, and noise generation of the system. It is shown that the system is effective in simulating the vibration of fetal movements, covering the full frequency and magnitude ranges of real FMV vibrations. The noise generation test shows that the system can effectively create scenarios with different signal-to-noise ratios for FMV detection. The system can facilitate the development of fetal movement monitoring systems and algorithms.Capnometry is a method to measure carbon dioxide (CO2) in exhaled gas and has been used to monitor patient's respiratory status. During moderate or deep sedation, monitoring for the presence of exhaled CO2 is recommended for evaluating the adequacy of ventilation. Oxygen administration is usually given to patients with a nasal cannula to avoid hypoxia during sedation. However, the flow of oxygen administration can interfere with CO2 measurement. We developed a nasal cannula type adapter called cap-ONE nasal adapter system based on the mainstream capnography which is designed to monitor CO2 while supplying oxygen. In this study, we evaluated the basic performance of the system as compared with a conventional device using a spontaneous breathing model. The cap-ONE nasal adapter system could accurately measure PetCO2 without being disturbed by oxygen flow and efficiently supply oxygen.Capnometry is a method to measure carbon dioxide (CO2) in exhaled gas and it has been used to monitor patient respiratory status. CO2 monitoring is also used for patients receiving non-invasive positive pressure ventilation (NPPV) therapy during mechanical ventilation. Ventilators actively dilute exhaled gas during non-invasive ventilation. In order to accurately measure end-tidal CO2, an adequate amount of expired gas needs to be filled in a CO2 measurement cell before expiratory positive airway pressure (EPAP) gas from the ventilator arrives to the cell. This is the reason why it is difficult to measure CO2 stably during non-invasive ventilation using the conventional CO2 measurement method. Therefore, we developed NPPV cap-ONE mask, which accurately measures CO2 in exhaled gas during non-invasive ventilation. In this study, we evaluated the basic performance of the NPPV cap-ONE mask system. The NPPV cap-ONE mask system could accurately measure CO2 in exhaled gas comparing to the conventional device in this study.This work presents a modelling approach to predict the blood pressure (BP) waveform time series during activities of daily living without the use of a traditional pressure cuff. A nonlinear autoregressive model with exogenous inputs (NARX) is implemented using artificial neural networks and trained to predict the BP waveform time series from electrocardiography (ECG) and forehead photoplethysmography (PPG) input signals. To broaden the range of blood pressures present in the training set, a protocol was implemented that included sitting, standing, walking, Valsalva manoeuvers, and static handgrip exercise. A five-minute interval of data in the sitting position at the end of the day was also used for training. The efficacy of the cuffless BP method for continuous BP estimation over 4.67 hours was evaluated on 3 participants for varying training data segments. A mean absolute error of 6.3 and 5.2 mmHg were achieved for systolic BP and diastolic BP estimates, respectively. Including static handgrips and Valsalva manoeuvers in the training dataset leads to better estimation of the higher ranges of BP observed throughout the day. The proposed method shows potential for estimating the range of BP experienced during activities of daily living.Clinical Relevance- Establishes a method for cuffless continuous blood pressure estimation during activities of daily living that can be used for continuous monitoring and acute hypertension detection.The US and European guidelines for the diagnosis and management of hypertension recommend the introduction of systematic home and night Blood Pressure (BP) monitoring. Fully-automated wearable devices can address the needs of patients and clinicians by improving comfort while achieving measurement accuracy. Often located at the wrist and based on indirect BP measurements, these devices must address the challenges of ambulatory scenarios. New validation strategies are needed, but little guidance has been published so far.In this work, we propose an experimental protocol for the validation of cuffless wrist BP monitors that addresses ambulatory environment challenges in a controlled experimental setting. The protocol assesses the robustness of the measurement for different body postures, the ability of the device to track BP changes, and its ability to deal with hydrostatic pressure changes induced by different arm heights.Performance testing using Aktiia Bracelet is provided as an illustration. The results of this pilot study indicate that the Aktiia Bracelet can generate accurate BP estimates for sitting and lying positions and is not affected by hydrostatic pressure perturbations.Clinical Relevance- Automated cuffless BP monitoring is opening a new chapter in the way patients are being diagnosed and managed. This paper provides a guidance on how to assess the clinical utility of such devices when used in different body positions.Visceral congestion and edema are important features of advanced heart failure. Monitoring the evolution of fluid content in the gastric wall might provide an index of the development of this phenomenon and therefore constitute an innovative marker to early detect acute decompensated heart failure episodes. The evolution of the fluid content in the gastric wall is measured using a device implanted in the submucosa layer of the fundic region of the stomach. The device composed of two electrodes measures the bioimpedance values that reflects the water content of the tissue.An in-vivo experiment in a pig was carried out to validate the feasibility of detecting the gastric bioimpedance variations during the development of an experimental acute visceral edema caused by an endotoxemic shock. Our preliminary results confirm the possibility to monitor the bioimpedance variations due to moderate changes in tissue water content (10%) with a two-electrode configuration device implanted in the submucosa of the stomach.We present an open-source, low-cost, portable, 128-channel bioamplifier module designed specifically for ambulatory, long-term (≥24 hr) monitoring of gastrointestinal (GI) electrical activity. The electronics hardware integrates stateof-the-art, commercial-off-the-shelf components on a custom PCB. Features include on-board data logging, wireless data streaming, subject motion monitoring, and stable operation up to the maximum 2 kHz/channel sampling rate tested. The new device operates for ≈ 30 hr continuously powered by a single 3.7 V, 2500 mAh LiPo battery. The 3D-printed ABS mechanical enclosure is robust and small (13.1 × 8.8 × 2.5 cm), so that the device can be carried in a standard Holter monitor pouch. Results from initial 128-channel, high spatial resolution body surface colon mapping experiments demonstrate the utility of this new device for GI applications. The new bioamplifier module could also be used for multichannel recording experiments in a variety of biomedical domains to study electrical activity patterns of the neuromuscular system (EMG), uterus (EHG), heart (ECG), and brain (EEG).In this paper, we have presented Turtulebot-assisted instantaneous heart rate (HR) estimator using camera based remote photoplethysmography. We used a Turtlebot with a camera to record human face. For the face detection, we used Haar Cascade algorithm. To increase the accuracy of the HR estimation, we combined a plane-orthogonal-to-skin (POS) model with finite state machine (FSM) framework. By combining POS and FSM framework, we achieved 1.08 bpm of MAE, which is the lowest error comparing to the state-of-art methods.Methods commonly used for reduction of motion artefacts in photoplethysmography employ accelerometry as a reference for adaptive filtering and signal processing. In this paper, we propose the use of an optical flow sensor to measure the relative displacement between a photoplethysmographic sensor and the measurement site. In order to evaluate the performances of this novel method, a wrist-worn device that enables simultaneous acquisition of physiological information and relative motion has been developed. The optical flow sensor provides a two-dimensional information source correlated with artefacts contained in the cardiac frequency band. Preliminary results show a clear correlation between motion recorded by the sensor and artefacts contained in the photoplethysmographic signal. In association with adaptive filtering, the proposed technique shows efficient reduction of motion artefacts during physical activity.Reflectance photoplethysmography is a widely employed method in personal health assessment devices. We developed a remote PPG system for obtaining the signal from palm skin. GW0742 manufacturer For the handle-mounted design, it is crucial to ensure accurate measurements under a range of skin temperatures. Under lower temperatures, green PPG was proven to provide superior signal quality in comparison to infrared PPG. However, since hemoglobin has maximum absorption in both green and blue parts of the spectrum, to ensure a stable performance of handle-mounted PPG system under different temperature conditions, it is worth exploring the PPG signal in both wavelengths. In our PPG system, TCS3472 Color Sensor was chosen as a photodetector. In distinction from video cameras with Bayer pattern, the TCS3472 has an equal number of R, G, and B sensing elements, thereby allowing the comparison of these wavelengths performance. Using the developed system, we compared green and blue PPG signals from six subjects in terms of amplitude and accuracy of heartbeat intervals estimation under two temperature conditions. According to our preliminary results, the performance of blue PPG was comparable to green PPG under both temperature conditions, suggesting further investigation with our system is worth conducting.When estimating the heart rate (HR) of an exerciser by using a photoplethysmographic (PPG) sensor, the PPG output is contaminated with motion artifact (MA) induced by his motion, resulting in erroneous HR. To cancel the MA in the PPG output, we have proposed a technique based on adaptive filter algorithm using an MA sensor. On the one hand, we have so far fixed the tap length of the adaptive filter algorithm for the sake of its simple implementation, but on the other hand, we have noticed that the tap length dynamically changes according to the type of sensor wearer, the intensity of exercise and so on. Therefore, in this paper, we propose an MA canceling-PPG HR sensor system based on a serially configured adaptive filter algorithm with variable tap length. Experimental results involving 13 subjects reveal that the MA canceling technique based on the proposed serial configuration outperforms that with a conventional parallel configuration, achieving the minimum root mean square error of 9.97 beats per minute with much less computational complexity.