BMC biomedical engineering最新文献

Aim: The aim of this study is to apply a novel hybrid framework incorporating a Vision Transformer (ViT) and bidirectional long short-term memory (Bi-LSTM) model for classifying physical activity intensity (PAI) in adults using gravity-based acceleration. Additionally, it further investigates how PAI and temporal window (TW) impacts the model' s accuracy.

Method: This research used the Capture-24 dataset, consisting of raw accelerometer data from 151 participants aged 18 to 91. Gravity-based acceleration was utilised to generate images encoding various PAIs. These images were subsequently analysed using the ViT-BiLSTM model, with results presented in confusion matrices and compared with baseline models. The model's robustness was evaluated through temporal stability testing and examination of accuracy and loss curves.

Result: The ViT-BiLSTM model excelled in PAI classification task, achieving an overall accuracy of 98.5% ± 1.48% across five TWs-98.7% for 1s, 98.1% for 5s, 98.2% for 10s, 99% for 15s, and 98.65% for 30s of TW. The model consistently exhibited superior accuracy in predicting sedentary (98.9% ± 1%) compared to light physical activity (98.2% ± 2%) and moderate-to-vigorous physical activity (98.2% ± 3%). ANOVA showed no significant accuracy variation across PAIs (F = 2.18, p = 0.13) and TW (F = 0.52, p = 0.72). Accuracy and loss curves show the model consistently improves its performance across epochs, demonstrating its excellent robustness.

Conclusion: This study demonstrates the ViT-BiLSTM model's efficacy in classifying PAI using gravity-based acceleration, with performance remaining consistent across diverse TWs and intensities. However, PAI and TW could result in slight variations in the model's performance. Future research should concern and investigate the impact of gravity-based acceleration on PAI thresholds, which may influence model's robustness and reliability.

Background: The ST response to high frequency EM heating may give an indication of rate of BF in underlying tissue. This novel method, which we have termed REFLO (Rapid Electromagnetic Flow) has potential for applications such as detection of PAD. The method utilizes the relationship between blood flow rate and tissue temperature increase during exposure to radio frequency (RF) energy. We are developing an REFLO device to screen for peripheral artery disease (PAD). PAD is characterized by impaired blood flow to the legs, as reflected in the skin microcirculation. The REFLO system incorporates a radio frequency transmitter and a compact transducer housing a micropatch antenna and an infrared (IR) temperature sensor. At high RF frequencies (> 6 GHz) tissue heating is confined to the skin, such that an indication of blood flow may be inferred from the temperature response to controlled heating. The objective of this study is to determine the extent to which the magnitude and depth of heating as well as device sensitivity are functions of (i) RF frequency and (ii) thickness of the dermal tissue layer.

Results: Results show that it is feasible to measure blood flow rate with REFLO technology. Surface temperature increases were found to be more dependent upon the magnitude of power absorption than location of absorption within the skin. While surface temperature response does depend upon radio wave frequency and thickness of the dermis layer, such dependencies are mild. Sensitivity to blood flow rate was found to be proportional to the magnitude of absorbed power.

Conclusion: Results show that it is feasible to discriminate between blood flow rates using REFLO technology at frequencies within the 10-94 GHz range. All frequencies analyzed produced similar levels of sensitivity to blood flow rate despite significant differences in penetration depth. These results are being used in the development of a preclinical prototype for quick and easy detection of asymptomatic PAD in humans.

Despite significant technological progress in prosthetic hands, a device with functionality akin to a biological extremity is far from realization. To better support the development of next-generation technologies, we investigated the grasping capabilities of clinically prescribable and commercially available (CPCA) prosthetic hands against those that are 3D-printed, which offer cost-effective and customizable solutions. Our investigation utilized the Anthropomorphic Hand Assessment Protocol (AHAP) as a benchtop evaluation of the multi-grasp performance of 3D-printed devices against CPCA prosthetic hands. Our comparison sample included three open-source 3D-printed prosthetic hands (HACKberry Hand, HANDi Hand, and BEAR PAW) and three CPCA prosthetic hands (Össur i-Limb Quantum, RSL Steeper BeBionic Hand V3, and Psyonic Ability Hand), along with including previously published AHAP data for four additional 3D-printed hands (Dextrus v2.0, IMMA, InMoov, and Limbitless). Our findings revealed a notable grasping performance disparity, with 3D-printed prostheses generally underperforming compared to their CPCA counterparts, specifically in cylindrical, diagonal volar, extension, and spherical grips. We propose that the observed performance shortfalls are likely attributed to the design or build quality of the 3D-printed prostheses, owing to the fact that 3D-printed hands often have a lower technology readiness level for widespread use. Addressing the limitations highlighted in this work and subsequent research will play a crucial role in refining the design and functionality of both 3D-printed and CPCA prosthetic devices.

Background: This study introduces a novel surgical instrument to reduce iatrogenic nerve injuries during procedures such as carpal tunnel and ulnar nerve decompression surgery. These injuries often result from direct damage to surrounding tissues by surgical instruments, whose designs have remained largely unchanged over the past decades. The novel device is a modified surgical forceps that has a deployable surgical scalpel that runs along a groove on the forceps. This design protects important anatomical structures while allowing fast dissection and cutting of fascial layers.

Methods: The process used to develop a novel instrument included computer-aided design (CAD) modeling, 3D printing for prototyping, and the fabrication of an aluminum prototype. Biomechanical testing was performed with the novel device, iris scissors, bandage scissors, and a scalpel on an MTS Static Materials Test System. The peak force to slide-cut, number of cut attempts, and percentage cut on first attempt were compared between the prototype and traditional surgical tools. The materials cut in testing were Ace™ bandage, stockinette, and gauze. Statistical analyses were performed using Welch's t-tests and Fisher's exact tests.

Results: Compared to conventional bandage and iris scissors, the novel surgical instrument required significantly less force to cut through an Ace™ bandage, stockinette, and gauze (p < 0.01). The number of cuts required to transect those same materials with the novel device was comparable to that of the scalpel and bandage scissors. Additionally, while there were no differences between the novel device and the other devices for an Ace™ bandage and stockinette, the novel device tended to cut a greater percentage of gauze in one pass than did the iris scissors.

Conclusion: The novel surgical instrument designed in this study required less force compared to conventional scissors, demonstrated cutting efficiency similar to that of a scalpel blade, and had more safety features than either instrument. This study highlights the value of collaboration between biomedical engineering and orthopedic surgery departments on innovation in medical technology, through which new technologies with improved design and functionality demonstrate the potential to reduce iatrogenic injuries.

Movement is a central behavior of daily living; thus lost or compromised movement due to disease, injury, or amputation causes enormous loss of productivity and quality of life. While prosthetics have evolved enormously over the years, restoring natural sensorimotor (SM) control via a prosthesis is a difficult problem which neuroengineering has yet to solve. With a focus on upper limb prosthetics, this perspective article discusses the neurophysiology of motor control under healthy conditions and after amputation, the development of upper limb prostheses from early generations to current state-of-the art sensorimotor neuroprostheses, and how postinjury changes could complicate prosthetic control. Current challenges and future development of smart sensorimotor neuroprostheses are also discussed.

Background: Restorative solutions designed for edentulous patients such as dentures and their accompanying denture adhesives operate in the complex and dynamic environment represented by human oral physiology. Developing material models accounting for the viscoelastic behavior of denture adhesives can facilitate their further optimization within that unique physiological environment. This study aims to statistically quantify the degree of significance of three physiological variables - namely: temperature, adhesive swelling, and pH - on denture adhesive mechanical behavior. Further, based on these statistical significance estimations, a previously-developed viscoelastic material modelling approach for such denture adhesives is further expanded and developed to capture these variables' effects on mechanical behavior.

Methods: In this study a comparable version of Denture adhesive Corega Comfort was analysed rheologically using the steady state frequency sweep tests. The experimentally derived rheological storage and loss modulus values for the selected physiological variables were statistically analyzed using multi parameter linear regression analysis and the Pearson's coefficient technique to understand the significance of each individual parameter on the relaxation spectrum of the denture adhesive. Subsequently, the parameters are incorporated into a viscoelastic material model based on Prony series discretization and time-temperature superposition, and the mathematical relationship for the loss modulus is deduced.

Results: The results of this study clearly indicated that the variation in both the storage and loss modulus values can be accurately predicted using the oral cavity physiological parameters of temperature, swelling ratio, and pH with an adjusted R² value of 0.85. The R² value from the multi-parameter regression analysis indicated that the predictor variables can estimate the loss and storage modulus with a reasonable accuracy for at least 85% of the rheologically determined continuous relaxation spectrum with a confidence level of 98%. The Pearson's coefficient for the independent variables indicated that temperature and swelling have a strong influence on the loss modulus, whereas pH had a weak influence. Based on statistical analysis, these mathematical relationships were further developed in this study.

Conclusions: This multi-parameter viscoelastic material model is intended to facilitate future detailed numerical investigations performed with implementation of denture adhesives using the finite element method.

Trial design: This study is a pilot randomized clinical trial aimed to investigate the effect of using Hip Exoskeleton Assistive (HEXA) robot compared to conventional physiotherapy on the quality of walking, disability, and quality of life of stroke patients with hemiplegia.

Methods: In this study, 24 patients were randomly assigned to the intervention group (robotic physiotherapy with HEXA robot), or control group (conventional physiotherapy). In each session, both groups received 30 min of conventional physiotherapy including electrotherapy and conventional exercises, and then the intervention group did gait training for 30 min with the HEXA robot and the control group for 30 min without the HEXA robot. The treatment program was 12 sessions, 3 times a week. Before the 1st and after the 12th sessions, both groups were evaluated for walking quality, disability, and quality of life.

Results: The results showed that the main effect of time was significant (P < 0.05) in all outcomes and patients in both groups achieved significant improvement in all outcomes after the intervention. The main effect of the group was also significant in the outcomes of 6MWT (P < 0.05) and TUG (P < 0.05), and the intervention group patients experienced more distance and speed in these two tests. This study was approved by the ethics committee of Mashhad University of Medical Sciences (IR.MUMS.FHMPM.REC.1400.079 dated 28th Jan 2022). The trial was registered with the clinical trials site of www.IRCT.ir (IRCT20210730052024N1) on January 28th 2022.

Conclusion: It seems that the HEXA robot can effectively improve walking capacity and speed.

This article aims to provide and implement a patient-specific seizure (for Intervention Time (IT) detection) prediction algorithm using non-invasive data to develop warning devices to prevent further patient injury and reduce stress. Employing algorithms with high initial data volume and computations time to increase the accuracy is an important problem in prediction issues. Consequently, reduction of calculations is met by applying only two effective EEG signal channels without manual removal of artifacts by visual inspection as the algorithm's input. Autoregression (AR) modeling and Cepstrum detect changes due to IT period. We carry out the goal of higher accuracy by increasing sensitivity to interictal epileptiform discharges or artifacts and reduce errors caused by them, taking advantage of the discrete wavelet transform and the comparison of two channels epochs by applying the median filter. Averaging and positive envelope methods are introduced to patient-specific thresholds become more differentiated as soon as possible and can be lead to sooner prediction. We examined this method on a mathematical model of adult epilepsy as well as on 10 patients with EEG data. The results of our experiments confirm that performance of the proposed approach in accuracy and average false prediction rate is superior to other algorithms. Simulation results have been shown the robustness of our proposed method to artifacts and errors, which is a step towards the development of real-time alarm devices by non-invasive techniques.

Background: Visualization of cancer during breast conserving surgery (BCS) remains challenging; the BCS reoperation rate is reported to be 20-70% of patients. An urgent clinical need exists for real-time intraoperative visualization of breast carcinomas during BCS. We previously demonstrated the ability of a prototype imaging device to identify breast carcinoma in excised surgical specimens following 5-aminolevulinic acid (5-ALA) administration. However, this prototype device was not designed to image the surgical cavity for remaining carcinoma after the excised lumpectomy specimen is removed. A new handheld fluorescence (FL) imaging prototype device, designed to image both excised specimens and within the surgical cavity, was assessed in a clinical trial to evaluate its clinical utility for first-in-human, real-time intraoperative imaging during index BCS.

Results: The imaging device combines consumer-grade imaging sensory technology with miniature light-emitting diodes (LEDs) and multiband optical filtering to capture high-resolution white light (WL) and FL digital images and videos. The technology allows for visualization of protoporphyrin IX (PpIX), which fluoresces red when excited by violet-blue light. To date, $n=17$ patients have received $20\frac{\text{mg}}{\text{kg}}$ bodyweight (BW) 5-ALA orally 2-4 h before imaging to facilitate the accumulation of PpIX within tumour cells. Tissue types were identified based on their colour appearance. Breast tumours in sectioned lumpectomies appeared red, which contrasted against the green connective tissues and orange-brown adipose tissues. In addition, ductal carcinoma in situ (DCIS) that was missed during intraoperative standard of care was identified at the surgical margin at <1 mm depth. In addition, artifacts due to the surgical drape, illumination, and blood within the surgical cavity were discovered.

Conclusions: This study has demonstrated the detection of a grossly occult positive margin intraoperatively. Artifacts from imaging within the surgical cavity have been identified, and potential mitigations have been proposed.

Trial registration: ClinicalTrials.gov Identifier: NCT01837225 (Trial start date is September 2010. It was registered to ClinicalTrials.gov retrospectively on April 23, 2013, then later updated on April 9, 2020, to reflect the introduction of the new imaging device.).