Medical & Biological Engineering & Computing

The effect of rotational degree and routine activity on the risk of collapse in transtrochanteric rotational osteotomy for osteonecrosis of the femoral head—a finite element analysis Abstract To explore the mechanical mechanism and provide preoperative planning basis for transtrochanteric rotational osteotomy (TRO) procedure, a joint-preserving procedure for osteonecrosis of the femoral head. Eleven TRO finite element femurs with the most common types of necrosis were analyzed under multi-loading conditions. Thereafter, we made a comprehensive evaluation by considering the anatomy characters, daily activities, and risk indicators contain necrosis expansion trend, necrotic blood supply pressure, and the risk of fracture. The risk of fracture (ROF) is the lowest when standing on feet and increases gradually during normal walking and walking upstairs and downstairs. Compared with posterior rotation, rotating forward keeps more elements at low risk. Additionally, the correlation analysis shows it has a strong negative correlation (R2 = 0.834) with the average modulus of the roof. TRO finally decreased the stress and energy effectively. However, the stress and strain energy arise when rotated posteriorly less than 120°. The comprehensive evaluation observed that rotating forward 90°could reduce the total risks to 64%. TRO is an effective technique to prevent collapse. For the anterior and superior large necrosis, we recommend to rotate forward 60° to 90° (more efficient) or backward 180°. The methodology followed in this study could provide accurate and personalize preoperative planning. Graphical Abstract A proximal femur was reconstructed and modified using Mimics from a series of computed tomography. The models were meshed after solidified and performed different osteotomy, and then assigned material based on the Hounsfield Unit from CT images. Finally, 44 different TRO finite element femurs were analyzed under multi-loading conditions and evaluated comprehensively.

Comments on “A novel high input impedance front-end for capacitive biopotential measurement” Abstract A front-end for biopotential sensing in wearable medical devices has been recently proposed which is claimed to provide 100 GΩ input impedance by manually matching two resistor pairs in a positive- and a negative-feedback loop around an operational amplifier (op amp); the cost being that the equivalent input noise voltage doubles with respect to a simple non-inverting amplifier. The ECG acquired with capacitive (sic) electrodes through a cotton shirt is presented as a proof of the performance of the proposed circuit. It turns out, however, that the analysis ignores op amp’s input capacitance hence the effort to achieve a very high input resistance seems futile. Further, cotton is highly hygroscopic hence not an appropriate dielectric, so that there is no proof that the electrodes tested were actually capacitive. This comment addresses these two problems and some additional conceptual and methodological inaccuracies found in the paper.

A new detection method for EMG activity monitoring Abstract This paper introduces a new approach for electromyography (EMG) activity monitoring based on an improved version of the adaptive linear energy detector (ALED), a widely used technique in voice activity detection. More precisely, we propose a modified ALED technique (named M-ALED) to improve the method’s robustness with respect to noise. To achieve this objective, M-ALED relies on the Teager-Kaiser operator for signal pre-conditioning to increase the SNR and uses the order statistics to gain robustness against the signal’s impulsiveness. We propose again to exploit the order statistics for the initial signal baseline estimation to deal with the cases where such information is unavailable. Finally, since M-ALED detects the signal’s activity at the frame level, we propose in a second stage to refine this detection (at the sample level) by using a constant false alarm rate (CFAR) approach leading to the fine M-ALED (FM-ALED) solution. The performance of FM-ALED is assessed via real and synthetic EMG signal recordings and the obtained results highlight its effectiveness as compared with the state-of-the-art methods (it reduces the mean error probability by a factor close to 2).

Pulse transit time based respiratory rate estimation with singular spectrum analysis Abstract Respiratory rate (RR) is an important vital sign which can be difficult to measure accurately and unobtrusively in routine clinical practice. Pulse transit time (PTT), on the other hand, is unobtrusive to collect from electrocardiogram (ECG) and photoplethysmogram (PPG) signals. Using PTT is a novel method to estimate and monitor blood pressure (BP) and RR. This study aimed to estimate continuous RR using PTT with singular spectrum analysis to extract respiratory components. The performance of this method was validated on 17 subjects who carried out spontaneous breathing and controlled deep breathing conditions. Three types of estimated RR parameters (average RR by power spectral density (PSD) (RRPSD), number of breaths (RR#), and instantaneous RR (RRinst)) were compared with the corresponding reference RR. The reference RR was collected using a respiratory belt. Our findings demonstrate that the PTT signal reliably tracked respiratory variation with a root mean square error of 0.84, 1.11, and 0.74 breaths/min for RRPSD, RR#, and RRinst estimations, respectively. Overall, RR estimated by PTT was more accurate than heart/pulse rate interval, QRS area, and PPG amplitude, which were also extracted from ECG and PPG. The results suggest that it may be feasible to use PTT as an estimation of RR and that ECG and PPG may be relied upon for monitoring not only RR but also BP and heart rate. Graphical abstract The Pulse Transit Time (PTT) based Respiratory Rate (RR) estimation with Singular Spectrum Analysis (SSA) provides a superior performance than the method with other respiratory indicators extracted from Electrocardiogram (ECG) or Photoplethysmogram (PPG)

Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks Abstract The aim of this study is to use a multilayer perceptron (MLP) artificial neural network (ANN) for phaseless imaging the human heel (modeled as a bilayer dielectric media: bone and surrounding tissue) and the calcaneus cross-section size and location using a two-dimensional (2D) microwave tomographic array. Computer simulations were performed over 2D dielectric maps inspired by computed tomography (CT) images of human heels for training and testing the MLP. A morphometric analysis was performed to account for the scatterer shape influence on the results. A robustness analysis was also conducted in order to study the MLP performance in noisy conditions. The standard deviations of the relative percentage errors on estimating the dielectric properties of the calcaneus bone were relatively high. Regarding the calcaneus surrounding tissue, the dielectric parameters estimations are better, with relative percentage error standard deviations up to ≈ 15%. The location and size of the calcaneus are always properly estimated with absolute error standard deviations up to ≈ 3 mm. Microwave tomography of the calcaneus using phaseless data. Simulations were inspired in Computed Tomography images from real heels (above). Inverse problem was solved using Multilayer Perceptron Artificial Neural Network (below).

Novel transcutaneous sensor combining optical tcPO 2 and electrochemical tcPCO 2 monitoring with reflectance pulse oximetry Abstract This study investigated the accuracy, drift, and clinical usefulness of a new optical transcutaneous oxygen tension (tcPO2) measuring technique, combined with a conventional electrochemical transcutaneous carbon dioxide (tcPCO2) measurement and reflectance pulse oximetry in the novel transcutaneous OxiVenT™ Sensor. In vitro gas studies were performed to measure accuracy and drift of tcPO2 and tcPCO2. Clinical usefulness for tcPO2 and tcPCO2 monitoring was assessed in neonates. In healthy adult volunteers, measured oxygen saturation values (SpO2) were compared with arterially sampled oxygen saturation values (SaO2) during controlled hypoxemia. In vitro correlation and agreement with gas mixtures of tcPO2 (r = 0.999, bias 3.0 mm Hg, limits of agreement − 6.6 to 4.9 mm Hg) and tcPCO2 (r = 0.999, bias 0.8 mm Hg, limits of agreement − 0.7 to 2.2 mm Hg) were excellent. In vitro drift was negligible for tcPO2 (0.30 (0.63 SD) mm Hg/24 h) and highly acceptable for tcPCO2 (− 2.53 (1.04 SD) mm Hg/12 h). Clinical use in neonates showed good usability and feasibility. SpO2-SaO2 correlation (r = 0.979) and agreement (bias 0.13%, limits of agreement − 3.95 to 4.21%) in healthy adult volunteers were excellent. The investigated combined tcPO2, tcPCO2, and SpO2 sensor with a new oxygen fluorescence quenching technique is clinically usable and provides good overall accuracy and negligible tcPO2 drift. Accurate and low-drift tcPO2 monitoring offers improved measurement validity for long-term monitoring of blood and tissue oxygenation. Graphical abstract

Automatic forensic identification using 3D sphenoid sinus segmentation and deep characterization Abstract Recent clinical research studies in forensic identification have highlighted the interest in sphenoid sinus anatomical characterization. Their pneumatization, well known as extremely variable in degrees and directions, could contribute to the radiologic identification, especially if dental records, fingerPrints, or DNA samples are not available. In this paper, we present a new approach for automatic person identification based on sphenoid sinus features extracted from computed tomography (CT) images of the skull. First, we present a new approach for fully automatic 3D reconstruction of the sphenoid hemisinuses which combines the fuzzy c-means method and mathematical morphology operations to detect and segment the object of interest. Second, deep shape features are extracted from both hemisinuses using a dilated residual version of a stacked convolutional auto-encoder. The obtained binary segmentation masks are thus hierarchically mapped into a compact and low-dimensional space preserving their semantic similarity. We finally employ the ℓ2 distance to recognize the sphenoid sinus and therefore identify the person. This novel sphenoid sinus recognition method obtained 100% of identification accuracy when applied on a dataset composed of 85 CT scans stemming from 72 individuals. Automatic Forensic Identification using 3D Sphenoid Sinus Segmentation and Deep Characterization from Dilated Residual Auto-Encoders

Implantable electrical stimulation bioreactor with liquid crystal polymer-based electrodes for enhanced bone regeneration at mandibular large defects in rabbit Abstract The osseous regeneration of large bone defects is still a major clinical challenge in maxillofacial and orthopedic surgery. Previous studies demonstrated that biphasic electrical stimulation (ES) stimulates bone formation; however, polyimide electrode should be removed after regeneration. This study presents an implantable electrical stimulation bioreactor with electrodes based on liquid crystal polymer (LCP), which can be permanently implanted due to excellent biocompatibility to bone tissue. The bioreactor was implanted into a critical-sized bone defect and subjected to ES for one week, where bone regeneration was evaluated four weeks after surgery using micro-CT. The effect of ES via the bioreactor was compared with a sham control group and a positive control group that received recombinant human bone morphogenetic protein (rhBMP)-2 (20 μg). New bone volume per tissue volume (BV/TV) in the ES and rhBMP-2 groups increased to 132% (p < 0.05) and 174% (p < 0.01), respectively, compared to that in the sham control group. In the histological evaluation, there was no inflammation within the bone defects and adjacent to LCP in all the groups. This study showed that the ES bioreactor with LCP electrodes could enhance bone regeneration at large bone defects, where LCP can act as a mechanically resistant outer box without inflammation. Graphical abstract To enhance bone regeneration, a bioreactor comprising collagen sponge and liquid crystal polymer-based electrode was implanted in the bone defect. Within the defect, electrical current pulses having biphasic waveform were applied from the implanted bioreactor.

Random forest–based classsification and analysis of hemiplegia gait using low-cost depth cameras Abstract Hemiplegia is a form of paralysis that typically has the symptom of dysbasia. In current clinical rehabilitations, to measure the level of hemiplegia gaits, clinicians often conduct subject evaluations through observations, which is unreliable and inaccurate. The Microsoft Kinect sensor (MS Kinect) is a widely used, low-cost depth sensor that can be used to detect human behaviors in real time. The purpose of this study is to investigate the usage of the Kinect data for the classification and analysis of hemiplegia gait. We first acquire the gait data by using a MS Kinect and extract a set of gait features including the stride length, gait speed, left/right moving distances, and up/down moving distances. With the gait data of 60 subjects including 20 hemiplegia patients and 40 healthy subjects, we employ a random forest–based classification approach to analyze the importances of different gait features for hemiplegia classification. Thanks to the over-fitting avoidance nature of the random forest approach, we do not need to have a careful control over the percentage of patients in the training data. In our experiments, our approach obtained the averaged classification accuracy of 90.65% among all the combinations of the gait features, which substantially outperformed state-of-the-art methods. The best classification accuracy of our approach is 95.45%, which is superior than all existing methods. Additionally, our approach also correctly reveals the importance of different gait features for hemiplegia classification. Our random forest–based approach outperforms support vector machine–based method and the Bayesian-based method, and can effectively extract gait features of subjects with hemiplegia for the classification and analysis of hemiplegia. Graphical Abstract Random Forest based Classsification and Analysis of Hemiplegia Gait using Low-cost Depth Cameras. Left: Motion capture with MS Kinect; Top-right: Random Forest Classsification based on the extracted gait features; Bottom-right: Sensitivity and specificity evaluation of the proposed classification approach.

Transcranial magnetic stimulation safety from operator exposure perspective Abstract A simulated model of a commercial transcranial magnetic stimulation (TMS) coil is analyzed to determine electromagnetic field (EMF) exposure for an operator while holding or adjusting the coil. Induced EMF strengths are calculated using a commercial figure-8 coil geometry and pulse configuration, with geometrical representations of the subject’s head and the operator’s head, torso, and hand. Exposure levels are compared to experimental results in the literature and international guidelines for occupational EMF exposure limits. Exposure limit guidelines of 0.8 V/m rms are exceeded at approximately 24.6 cm from the coil for the torso model and at 20.3 cm for the head model measured perpendicular to the plane of the coil. In the plane of the coil, the operator can approach closer without exceeding guidelines. The results in the hand model along the edge of the coil give 9.9 V/m and 88.5 V/m for average and peak field strength, respectively. A discussion of the potential consequences of operator exposure to fields exceeding published guidelines concludes that since the guidelines are only concerned with acute effects and do not suggest any potential chronic effects, occupational exposure in the context of delivering TMS treatment may be considered reasonable. Graphical abstract A model of an operator’s head/torso was moved in space relative to a standard TMS coil and subject. Positions at which safety guidelines are exceeded were calculated. The maximum induced electric field was also calculated in a hand model placed in a position commonly used to hold TMS coils during treatments.