Electrical impedance tomography: a potential tool for intraoperative imaging of the tongue base

The presence of a tumor in the tongue is a pathology that requires surgical intervention from a certain stage. This type of surgery is difficult to perform because of the limited space available around the base of the tongue for the insertion of surgical tools. During the procedure, the surgeon has to stretch and then fix the tongue firmly in order to optimize the available space and prevent tissue movement. As a result, the preoperative images of the inside of the tongue no longer give a reliable indication of the position and shape of the cancerous tissue due to the deformation of the overall tissue in the area. Thus, new images are needed during the operation, but are very difficult to obtain using conventional techniques due to the presence of surgical tools. Electrical Impedance Tomography (EIT) is an imaging technique that maps the resistivity or difference of resistivity of biological tissues from electrical signals. The small size of the electrodes makes it a potentially interesting tool to obtain intraoperative images of the inside of the tongue. In this paper, the possibility of using EIT for this purpose is investigated. A detection method is proposed, including an original configuration of the electrodes, consistent with the anatomical specificities of the tongue. The proposed method is studied in simulation and then a proof of concept is obtained experimentally on a 3D printed test tank filled with saline solution and plant fibres.

An efficient and fast multi-band focused bioimpedance solution with EIT-based reconstruction for pulmonary embolism assessment: a simulation study from massive to segmental blockage

Objective: Pulmonary embolism (PE) is an acute condition that blocks the perfusion to the lungs and is a common complication of Covid-19. However, PE is often not diagnosed in time, especially in the pandemic time due to complicated diagnosis protocol. In this study, a non-invasive, fast and efficient bioimpedance method with the EIT-based reconstruction approach is proposed to assess the lung perfusion reliably. Approach: Some proposals are presented to improve the sensitivity and accuracy for the bioimpedance method: (1) a new electrode configuration and focused pattern to help study deep changes caused by PE within each lung field separately, (2) a measurement strategy to compensate the effect of different boundary shapes and varied respiratory conditions on the perfusion signals and (3) an estimator to predict the lung perfusion capacity, from which the severity of PE can be assessed. The proposals were tested on the first-time simulation of PE events at different locations and degrees from segmental blockages to massive blockages. Different object boundary shapes and varied respiratory conditions were included in the simulation to represent for different populations in real measurements. Results: The correlation between the estimator and the perfusion was very promising (R = 0.91, errors < 6%). The measurement strategy with the proposed configuration and pattern has helped stabilize the estimator to non-perfusion factors such as the boundary shapes and varied respiration conditions (3-5% errors). Significance: This promising preliminary result has demonstrated the proposed bioimpedance method’s capability and feasibility, and might start a new direction for this application.

How reliable is measurement of posture during sleep: real-world measurement of body posture and movement during sleep using accelerometers

Objective Understanding sleeping behaviours could improve prevention and treatment of sleep problems and associated health conditions. This study aimed to evaluate a method to assess body posture and movement during sleep using trunk-worn accelerometers for 28 days. Approach Participants (50 adults with low back pain (66% female); aged 32(±9) years) wore two activPAL-micro sensors (thigh, trunk) during their normal daily life for 28 consecutive days. Parameters related to body posture (e.g., time spent lying supine or prone) and movement (e.g., number of turns) during sleep were calculated for each night. Average values for each parameter were identified for different periods, the Spearman-Brown Prophecy Formula was used to estimate the minimum number of nights required to obtain a reliable estimate of each parameter, and repeatability of measures between different weeks was calculated. Main Results Participants spent 8.1(±0.8) hours asleep and most time (44%) was spent in a supine posture. The minimum number of nights required for reliable estimates varied between sleep parameters, range 4-21 nights. The most stable parameters (i.e., requiring less than seven nights) were “average activity”, “no. of turns”, “time spent prone”, and “posture changes in the first hour”. Some measures differed substantially between weeks. Significance Most sleep parameters related to body posture and movement require a week or more of monitoring to provide reliable estimates of behaviour over one month. Notably, one week may not reflect behaviour in another week, and the time varying nature of sleep needs to be considered.

A conceptual model for changes in finger photoplethysmograph signals caused by hand posture and isothermic regulation

Objective. To observe changes in baseline and pulsatile light absorbance (photoplethysmograph, PPG) in the finger-tip, by raising the hand above the horizontal plane in recumbent subjects. We applied current knowledge of the circulation to the finger-tip, particularly arteriovenous anastomoses (AVAs), and the physiology of the venous circulation. Approach. We studied healthy young volunteers in a quiet thermoneutral environment. A finger plethysmograph on the non-dominant hand recorded transmission of red and infra-red light, and the values were converted into absorbance to allow comparisons within and between subjects. Breathing movements were recorded unobtrusively to assess any effect on absorbance and the pulse amplitude of the signals. All body movements were passive: the study arm was elevated in a trough to about 40° above the horizontal plane. The following conditions were studied, each for 15 minutes, using the last 10 minutes for analysis: recumbent, study arm elevated, study arm horizontal, and both legs elevated by 40°. Main results. There was a substantial time-related effect, and considerable variation between subjects. Arm elevation reduced red light absorbance and increased the range of amplitudes of the PPG waveform: only in subjects with large absorbances, did waveform amplitude increase. The other main effect was that spontaneous, thermoregulatory decreases in absorbance were associated with decreases in waveform amplitude. Significance. Finger-tip vessels distend with blood when AVAs open. The vessels pulsate more strongly if venous collapse allows the vessels to become more compliant. The postcapillary circulation is likely to be an important source of pulsation.

Automatic detection of respiratory events during sleep from Polysomnography data using Layered Hidden Markov Model

Objective. Sleep apnea is a serious respiratory disorder, which is associated with increased risk factors for cardiovascular disease. Many studies in recent years have been focused on automatic detection of sleep apnea from polysomnography (PSG) recordings, however, detection of subtle respiratory events named Respiratory Event Related Arousals (RERAs) that do not meet the criteria for apnea or hypopnea is still challenging. The objective of this study was to develop automatic detection of sleep apnea based on Hidden Markov Models (HMMs) which are probabilistic models with the ability to learn different dynamics of the real time-series such as clinical recordings. Approach. In this study, a hierarchy of HMMs named Layered HMM was presented to detect respiratory events from PSG recordings. The recordings of 210 PSGs from Massachusetts General Hospital’s database were used for this study. To develop detection algorithms, extracted feature signals from airflow, movements over the chest and abdomen, and oxygen saturation in blood (SaO2) were chosen as observations. The respiratory disturbance index (RDI) was estimated as the number of apneas, hypopneas, and RERAs per hour of sleep. Main results. The best F1 score of the event by event detection algorithm was between 0.22±0.16 and 0.70±0.08 for different groups of sleep apnea severity. There was a strong correlation between the estimated and the PSG-derived RDI (R2=0.91, p<0.0001). The best recall of RERA detection was achieved 0.45±0.27. Significance. The results showed that the layered structure can improve the performance of the detection of respiratory events during sleep.

The effect of passive lower limb training on heart rate asymmetry

Objective: Heart rate asymmetry (HRA) is an approach for quantitatively assessing the uneven distribution of heart rate accelerations and decelerations for sinus rhythm. We aimed to investigate whether automatic regulation led to HRA alternation during passive lower limb training. Methods: Thirty healthy participants were recruited in this study. The protocol included a baseline (Pre-E) and three passive lower limb training trials (E1, E2 and E3) with a randomized order. Several variance-based HRA variables were established. Heart rate variability (HRV) parameters, i.e., mean RR, SDNN, RMSSD, LF (n.u.), HF (n.u.) and VLF (ms2), and HRA variables, i.e., SD1a, SD1d, SD2a, SD2d, SDNNa and SDNNd, were calculated by using 5-min RR time series, as well as the normalized HRA variables, i.e., C1a, C1d, C2a, C2d, Ca and Cd. Results: Our results showed that the performance of HRA was distinguished. The normalized HRA was observed with significant changes in E1, E2 and E3 compared to Pre -E. Moreover, parts of non-normalized HRA variables correlated with HRV parameters, which indicated that HRA might benefit in assessing cardiovascular modulation in passive lower limb training. Conclusions: In summary, this study suggested that passive training led to significant HRA alternation and the application of HRA gave us the possibility for autonomic assessment.

Simplifying the hardware requirements for fast neural EIT of peripheral nerves

Objective: The main objective of this study was to assess the feasibility of lowering the hardware requirements for fast neural EIT in order to support the distribution of this technique. Specifically, the feasibility of replacing the commercial modules present in the existing high-end setup with compact and cheap customized circuitry was assessed. Approach: Nerve EIT imaging was performed on rat sciatic nerves with both our standard ScouseTom setup and a customized version in which commercial benchtop current sources were replaced by custom circuitry. Electrophysiological data and images collected in the same experimental conditions with the two setups were compared. Data from the customized setup was subject to a down-sampling analysis to simulate the use of a recording module with lower specifications. Main results: Compound action potentials (573±287µV and 487±279µV, p=0.28) and impedance changes (36±14µV and 31±16µV, p=0.49) did not differ significantly when measured using commercial high-end current sources or our custom circuitry, respectively. Images reconstructed from both setups showed neglibile (<1voxel, i.e. 40µm) difference in peak location and a high degree of correlation (R2=0.97). When down-sampling from 24 to 16 bits ADC resolution and from 100KHz to 50KHz sampling frequency, signal-to-noise ratio showed acceptable decrease (<-20%), and no meaningful image quality loss was detected (peak location difference <1voxel, pixel-by-pixel correlation R2=0.99). Significance: The technology developed for this study greatly reduces the cost and size of a fast neural EIT setup without impacting quality and thus promotes the adoption of this technique by the neuroscience research community.

Progressive evaluation in spectroscopic sensors for non-invasive blood haemoglobin analysis - a review

Frequent monitoring of haemoglobin concentration is highly recommended by physicians to diagnose anaemia and polycythemia Vera. Moreover, Some other conditions also demand assessment of haemoglobin, and these conditions are blood loss, before blood donation, during pregnancy, preoperative, perioperative and postoperative conditions. Cyanmethaemoglobin/haemiglobincyanide method, portable haemoglobinometers and haematology analyzers are few standard methods to diagnose mentioned ailments. However, discomfort, delay and risk of infection are typical limitations of traditional measuring solutions. These limitations create the necessity to develop a non-invasive haemoglobin monitoring technique for a better lifestyle. Various methods and products are already developed and popular due to their non-invasiveness; however, invasive solutions are still considered as the reference standard method. Therefore, this review summarizes the attributes of existing non-invasive solutions. These attributes are finalized as brief details, accuracy, optimal benefits, and research challenges for exploring potential gaps, advancements and possibilities to consider as futuristic alternative methodologies. Non-invasive total haemoglobin assessing techniques are mainly based on optical spectroscopy (reflectance/transmittance) or digital photography or spectroscopic imaging in spot check/continuous monitoring mode. In all these techniques, we have noticed that there is a need to consider different light conditions, motion artefacts, melanocytes, other blood constituents, smoking and precise fixing of the sensor from the sensing spot for exact formulation. Moreover, based on careful and critical analysis of outcomes, none of these techniques or products is used independently or intended to replace invasive laboratory testing. Therefore there is a requirement for a more accurate technique that can eliminate the requirement of blood samples and likely end up as a reference standard method.

CARL: a running recognition algorithm for free-living accelerometer data

Wearable accelerometers hold great promise for physical activity epidemiology and sports biomechanists. However, identifying and extracting data from specific physical activities, such as running, remains challenging. Objective: To develop and validate an algorithm to identify bouts of running in raw, free-living accelerometer data from devices worn at the wrist or torso (waist, hip, chest). Approach: The CARL (continuous amplitude running logistic) classifier identifies acceleration data with amplitude and frequency characteristics consistent with running. The CARL classifier was trained on data from 31 adults wearing accelerometers on the waist and wrist, then validated on free-living data from 30 new, unseen subjects plus 166 subjects from previously-published datasets using different devices, wear locations, and sample frequencies. Main Results: On free-living data, the CARL classifier achieved mean accuracy (F1 score) of 0.984 (95% confidence interval 0.962-0.996) for data from the waist and 0.994 (95% CI 0.991-0.996) for data from the wrist. In previously-published datasets, the CARL classifier identified running with mean accuracy (F1 score) of 0.861 (95% CI 0.836-0.884) for data from the chest, 0.911 (95% CI 0.884-0.937) for data from the hip, 0.916 (95% CI 0.877-0.948) for data from the waist, and 0.870 (95% CI 0.834-0.903) for data from the wrist. Misclassification primarily occurred during activities with similar torso acceleration profiles to running, such as rope jumping and elliptical machine use. Significance: The CARL classifier can accurately identify bouts of running as short as three seconds in free-living accelerometry data. An open-source implementation of the CARL classifier is available at <<GITHUBURL>>.

Quantifying tidal expiratory flow limitation using a vector-based analysis technique

Objective: Tidal expiratory flow limitation (EFLT) is commonly identified by tidal breaths exceeding the forced vital capacity (FVC) loop. This technique, known as the Hyatt method, is limited by the difficulties in defining the FVC and tidal flow-volume (TV) loops. The vector-based analysis (VBA) technique described and piloted in this manuscript identifies and quantifies EFLT as tidal breaths that conform to the contour of the FVC loop. Approach: The FVC and TV loops are interpolated to generate uniformly spaced plots. VBA is performed to determine the smallest vector difference between each point on the FVC and TV curves, termed the flow reserve vector (FRV). From the FVC point yielding the lowest FRV, the tangential angles of the FVC and TV segments are recorded. If the TV and FVC loops become parallel, the difference between the tangential angles tends towards zero. We infer EFLT as parallel TV and FVC segments where the FRV is <0.1 and the tangential angle is within ±18 degrees for ≥5% of TV. EFLT is quantified by the percent of TV loop fulfilling these criteria. We compared the presence and degree of EFLT at rest and during peak exercise using the Hyatt method and our VBA technique in 25 healthy subjects and 20 subjects with moderate-severe airflow obstruction. Main results: Compared to the Hyatt method, our VBA technique reported a significantly lower degree of EFLT in healthy subjects during peak exercise, and in obstructed subjects at rest and during peak exercise. In contrast to the Hyatt method, our VBA technique re-classified five subjects (one in the healthy group and four in the obstructed group) as demonstrating EFLT. Significance: Our VBA technique provides an alternative approach to determine and quantify EFLT which may reduce the overestimation of the degree EFLT and more accurately identify subjects experiencing EFLT.