Technology and Health Care - Volume Pre-press, issue Pre-press
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Technology and Health Care is intended to serve as a forum for the presentation of original articles and technical notes, observing rigorous scientific standards. Furthermore, upon invitation, reviews, tutorials, discussion papers and minisymposia are featured.
The following types of contributions and areas are considered:
1. Original articles:
Technology development in medicine: New concepts, procedures and devices associated with the use of technology in medical research and clinical practice are presented to a readership with a widespread background in engineering and/or medicine.
Significance of medical technology and informatics for healthcare: The appropriateness, efficacy and usefulness deriving from the application of engineering methods, devices and informatics in medicine and with respect to public health are discussed.
2. Technical notes:
Short communications on novel technical developments with relevance for clinical medicine.
3. Reviews and tutorials (upon invitation only):
Tutorial and educational articles for persons with a primarily medical background on principles of engineering with particular significance for biomedical applications and vice versa are presented.
4. Minisymposia (upon invitation only):
Under the leadership of a Special Editor, controversial issues relating to healthcare are highlighted and discussed by various authors.
Abstract: BACKGROUND: Resting tremor is an essential characteristic in patients suffering from Parkinson’s disease (PD). OBJECTIVE: Quantification and monitoring of tremor severity is clinically important to help achieve medication or rehabilitation guidance in daily monitoring. METHODS: Wrist-worn tri-axial accelerometers were utilized to record the long-term acceleration signals of PD patients with different tremor severities rated by Unified Parkinson’s Disease Rating Scale (UPDRS). Based on the extracted features, three kinds of classifiers were used to identify different tremor severities. Statistical tests were further designed for the feature analysis. RESULTS: The support vector…machine (SVM) achieved the best performance with an overall accuracy of 94.84%. Additional feature analysis indicated the validity of the proposed feature combination and revealed the importance of different features in differentiating tremor severities. CONCLUSION: The present work obtains a high-accuracy classification in tremor severity, which is expected to play a crucial role in PD treatment and symptom monitoring in real life.
Abstract: BACKGROUND: In the past ten years, liver biopsies have been used as a method to accurately diagnose the stage of fibrosis. OBJECTIVE: This study aimed to evaluate whether body position and exercise affect the measurement of liver Young’s modulus of healthy volunteers by real-time shear wave elastography (RT-SWE). Methods: RT-SWE was used to measure liver Young’s modulus in the supine and left lateral positions of 70 healthy volunteers at rest and measure the liver Young’s modulus in the lying position before exercise, and at zero, five, and ten minutes of rest after exercise.…RESULTS: The liver Young’s modulus in the left lateral position was significantly higher than in the supine position (P < 0.05), and the measured value in the supine position was more stable than the left lateral position. The liver Young’s modulus measured at zero minutes after exercise was significantly higher than that measured before exercise (P < 0.05). The liver Young’s modulus measured at five minutes after exercise was significantly higher than that measured at zero minutes after exercise (P < 0.05) and was not statistically different from the measured value before exercise (P > 0.05). The liver Young’s modulus measured at ten minutes after exercise was significantly higher from that measured at zero minutes after exercise (P < 0.05) and was not statistically different from the measured value at five minutes after exercise (P > 0.05). CONCLUSION: Body position and exercise have a significant impact on the measurement of liver Young’s modulus. It is recommended that the examinees take a supine position during the measurement, and measurement should be conducted at least ten minutes after exercise.
Abstract: BACKGROUND: The exoskeleton for lower limb rehabilitation is an uprising field of robot technology. However, since it is difficult to achieve all the optimal design values at the same time, each lower extremity exoskeleton has its own focus. OBJECTIVE: This study aims to develop a modular lightweight lower extremity exoskeleton (MOLLEE) with novel compliant ankle joints, and evaluate the movement performance through kinematics analysis. METHODS: The overall structure of the exoskeleton was proposed and the adjustable frames, active joint modules, and compliant ankle joints were designed. The forward and inverse kinematics models were…established based on the geometric method. The theoretical models were validated by numerical simulations in ADAMS, and the kinematic performance was demonstrated through walking experiments. RESULTS: The proposed lower extremity offers six degrees of freedom (DoF). The exoskeleton frame was designed adjustable to fit wearers with a height between 1.55 m and 1.80 m, and waist width from 37 cm to 45 cm. The joint modules can provide maximum torque at 107 Nm for adequate knee and hip joint motion forces. The compliant ankle can bear large flexible deformation, and the relationship between its angular deformation and the contact force can be fitted with a quadratic polynomial function. The kinematics models were established and verified through numerical simulations, and the walking experiments in different action states have shown the expected kinematic characteristics of the designed exoskeleton. CONCLUSIONS: The proposed MOLLEE exoskeleton is adjustable, modular, and compliant. The designed adjustable frame and compliant ankle can ensure comfort and safety for different wearers. In addition, the kinematics characteristics of the exoskeleton can meet the needs of daily rehabilitation activities.
Abstract: BACKGROUND: Addressing intensity inhomogeneity is critical in magnetic resonance imaging (MRI) because associated errors can adversely affect post-processing and quantitative analysis of images (i.e., segmentation, registration, etc.), as well as the accuracy of clinical diagnosis. Although several prior methods have been proposed to eliminate or correct intensity inhomogeneity, some significant disadvantages have remained, including alteration of tissue contrast, poor reliability and robustness of algorithms, and prolonged acquisition time. OBJECTIVE: In this study, we propose an intensity inhomogeneity correction method based on volume and surface coils simultaneous reception (VSSR). METHODS: The VSSR method comprises…of two major steps: 1) simultaneous image acquisition from both volume and surface coils and 2) denoising of volume coil images and polynomial surface fitting of bias field. Extensive in vivo experiments were performed considering various anatomical structures, acquisition sequences, imaging resolutions, and orientations. In terms of correction performance, the proposed VSSR method was comparatively evaluated against several popular methods, including multiplicative intrinsic component optimization and improved nonparametric nonuniform intensity normalization bias correction methods. RESULTS: Experimental results show that VSSR is more robust and reliable and does not require prolonged acquisition time with the volume coil. CONCLUSION: The VSSR may be considered suitable for general implementation.
Keywords: Intensity inhomogeneity correction, volume and surface coil simultaneously received, magnetic resonance imaging
Abstract: BACKGROUND: Traditional healthcare is centred around providing in-hospital services using hospital owned medical instruments. The COVID-19 pandemic has shown that this approach lacks flexibility to insure follow-up and treatment of common medical problems. In an alternative setting adapted to this problem, participatory healthcare can be considered centred around data provided by patients owning and operating medical data collection equipment in their homes. OBJECTIVE: In order to trigger such a shift reliable and price attractive devices need to become available. Snoring, as a human sound production during sleep, can reflect sleeping behaviour and indicate sleep problems as…an element of the overall health condition of a person. METHODS: The use of off-the-shelf hardware from Internet of Things platforms and standard audio components allows the development of such devices. A prototype of a snoring sound detector with this purpose is developed. RESULTS: The device, controlled by the patient and with specific snoring recording and analysing functions is demonstrated as a model for future participatory healthcare. CONCLUSIONS: Design of monitoring devices following this model could allow market introduction of new equipment for participatory healthcare, bringing a care complementary to traditional healthcare to the reach of patients, and could result in benefits from enhanced patient participation.
Keywords: Snoring, participatory healthcare, sleep analysis, internet of things, e-health
Abstract: BACKGROUND: Autistic Spectrum Disorder (ASD) is a neurodevelopment condition that is normally linked with substantial healthcare costs. Typical ASD screening techniques are time consuming, so the early detection of ASD could reduce such costs and help limit the development of the condition. OBJECTIVE: We propose an automated approach to detect autistic traits that replaces the scoring function used in current ASD screening with a more intelligent and less subjective approach. METHODS: The proposed approach employs deep neural networks (DNNs) to detect hidden patterns from previously labelled cases and controls, then applies the knowledge…derived to classify the individual being screened. Specificity, sensitivity, and accuracy of the proposed approach are evaluated using ten-fold cross-validation. A comparative analysis has also been conducted to compare the DNNs’ performance with other prominent machine learning algorithms. RESULTS: Results indicate that deep learning technologies can be embedded within existing ASD screening to assist the stakeholders in the early identification of ASD traits. CONCLUSION: The proposed system will facilitate access to needed support for the social, physical, and educational well-being of the patient and family by making ASD screening more intelligent and accurate.
Keywords: Autism, ASD screening, detection systems, machine learning, medical screening, deep neural network
Abstract: BACKGROUND: Trunk control ability is an important component of functional independence after the onset of stroke. Recently, it has been reported that robot-assisted functional training is effective for stroke patients. However, most studies on robot-assisted training have been conducted on upper and lower extremities. OBJECTIVE: The purpose of this study was to evaluate the effects of robot-assisted trunk control training on trunk postural control and balance ability in stroke patients. METHODS: Forty participants with hemiparetic stroke were recruited and randomly divided into two groups: the RT (robot-assisted trunk control training) group (n =…20) and the control group (n = 20). All participants underwent 40 sessions of conventional trunk stabilization training based on the Bobath concept (for 30 minutes, five-times per week for 8 weeks). After to each training session, 15 minutes of robotassisted trunk control training was given in the RT group, whereas the control group received stretching exercise for the same amount of time. Robot-assisted trunk control training was conducted in three programs: sitting balance, sit-to stand, and standing balance using a robot system specially designed to improve trunk control ability. To measure trunk postural control ability, trunk impairment scale (TIS) was used. Center of pressure (COP) distance, limits of stability (LOS), Berg Balance Scale (BBS) and functional reach test (FRT) were used to analyze balance abilities. RESULTS: In TIS, COP distance, LOS, BBS and FRT, there were significant improvements in both groups after intervention. More significant changes were shown in the RT group than the control group (p < 0.05). CONCLUSIONS: Our findings indicate that robot-assisted trunk control training is beneficial and effective to improve trunk postural control and balance ability in stroke patients. Therefore robot-assisted training may be suggested as an effective intervention to improve trunk control ability in patients with stroke.
Abstract: BACKGROUND: Pulmonary metastasis is the most frequent cause of death in osteosarcoma (OS) patients. Recently, several bioinformatics studies specific to pulmonary metastatic osteosarcoma (PMOS) have been applied to identify genetic alterations. However, the interpretation and reliability of the results obtained were limited for the independent database analysis. OBJECTIVE: The expression profiles and key pathways specific to PMOS remain to be comprehensively explored. Therefore, in our study, three original datasets of GEO database were selected. METHODS: Initially, three microarray datasets (GSE14359, GSE14827, and GSE85537) were downloaded from the GEO database. Differentially expressed genes (DEGs)…between PMOS and nonmetastatic osteosarcoma (NMOS) were identified and mined using DAVID. Subsequently, GO and KEGG pathway analyses were carried out for DEGs. Corresponding PPI network of DEGs was constructed based on the data collected from STRING datasets. The network was visualized with Cytoscape software, and ten hub genes were selected from the network. Finally, survival analysis of these hub genes also used the TARGET database. RESULTS: In total, 569 upregulated and 1238 downregulated genes were filtered as DEGs between PMOS and NMOS. Based on the GO analysis result, these DEGs were significantly enriched in the anatomical structure development, extracellular matrix, biological adhesion, and cell adhesion terms. Based on the KEGG pathway analysis result, these DEGs were mainly enriched in the pathways in cancer, PI3K-Akt signaling, MAPK signaling, focal adhesion, cytokine-cytokine receptor interaction, and IL-17 signaling. Hub genes (ANXA1 and CXCL12) were significantly associated with overall survival time in OS patient. CONCLUSION: Our results may provide new insight into pulmonary metastasis of OS. However, experimental studies remain necessary to elucidate the biological function and mechanism underlying PMOS.
Abstract: BACKGROUND: Electromyographic systems are widely used in scientific and clinical practice. The reproducibility and reliability of these measures are crucial when conducting scientific research and collecting experimental data.
Abstract: BACKGROUND: The analysis of brain activity in different conditions is an important research area in neuroscience. OBJECTIVE: This paper analyzed the correlation between the brain and skin activities in rest and stimulations by information-based analysis of electroencephalogram (EEG) and galvanic skin resistance (GSR) signals. METHODS: We recorded EEG and GSR signals of eleven subjects during rest and auditory stimulations using three pieces of music that were differentiated based on their complexity. Then, we calculated the Shannon entropy of these signals to quantify their information contents. RESULTS: The results showed that…music with greater complexity has a more significant effect on altering the information contents of EEG and GSR signals. We also found a strong correlation (r = 0.9682) among the variations of the information contents of EEG and GSR signals. Therefore, the activities of the skin and brain are correlated in different conditions. CONCLUSION: This analysis technique can be utilized to evaluate the correlation among the activities of various organs versus brain activity in different conditions.