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: Transcranial direct current stimulation (tDCS) has a considerable advantage in the rehabilitation treatment of dysphagia. OBJECTIVE: The purpose of this study was to explore the effect of tDCS combined with respiratory training on dysphagia in post-stroke patients. METHODS: From December 2017 to January 2019, 64 post-stroke patients who were hospitalized in the Department of Neurology of the Second Hospital of Hebei Medical University were enrolled in this study. They were randomly divided into control and treatment groups (n = 32). Patients in the two groups received routine…swallowing rehabilitation training and respiratory training. On this basis, the patients in the treatment group received tDCS. The anode was placed in the movement area of the pharyngeal cortex on the unaffected side of the patients’ bodies, and the cathode was placed in the upper orbital orbit on the opposite side. The current intensity was 1.5 mA, 20 min/time, 1 time/d, and 6 d/w. Before and after the treatment, the water swallow text, functional oral intake scale (FOIS), forced vital capacity (FVC) and peak expiratory flow (PEF) were assessed, and the correlation among them was evaluated. RESULTS: There were no differences in all indexes before and after treatment. After treatment, water swallow text, FOIS, FVC and PEF were all better than before treatment, and the clinical efficacy in the treatment group was significantly better than that in the control group. FVC and PEF were positively correlated with water swallow text and FOIS. CONCLUSION: tDCS combined with respiratory training may have a significant therapeutic effect on dysphagia in post-stroke patients.
Keywords: Transcranial direct current stimulation, respiratory training, dysphagia, stroke
Abstract: BACKGROUND: Soluble urokinase plasminogen activator receptor (suPAR) and tumor necrosis factor-alpha (TNF-α ) are inflammatory biomarkers. No studies have yet assessed the suPAR levels in relation with TNF-α in the peri-implant sulcular fluid (PISF) among cigarette smokers and non-smokers with peri-implantitis. OBJECTIVE: The aim was to evaluate PISF levels of suPAR, and TNF-α among cigarette smokers and non-smokers with and without peri-implantitis. METHODS: Sixty male patients with peri-implantitis were included. There were 20 cigarette smokers and 20 and non-smokers with peri-implantitis (Groups 1 and 2),…and 20 non-smokers without peri-implantitis (Group 3). Demographic data and information related to cigarette smoking was recorded. Peri-implant clinicoradiographic parameters (plaque index [PI], gingival index [GI], probing depth [PD] and crestal bone loss [CBL]) were assessed. The PISF samples were collected and levels of suPAR and TNF-α were measured. Sample-size estimation was performed and all parameters were statistically assessed. Level of significance was set at P < 0.05. RESULTS: Sixty individuals were included in Groups 1, 2 and 3 (20 in each). Peri-implant PI (P < 0.01), PD (P < 0.01) and mesial (P < 0.01) and distal (P < 0.01) CBL were significantly higher in Group 1 than in Groups 2 and 3. The PISF volume (P < 0.01) and suPAR (P < 0.01) and TNF-α levels (P < 0.01) were significantly higher in Groups 1 and 2 than in Group 3. There was no difference in PISF volume and suPAR and TNF-α levels between patients in Groups 1 and 2. In Group 2, there was a statistically significant correlation between peri-implant PD and PISF suPAR and TNF-α levels (P < 0.01). The suPAR and TNF-α levels are expressed in high concentrations in the PISF of smokers and non-smokers with peri-implantitis compared with non-smokers without peri-implantitis. CONCLUSION: In non-smokers, PISF suPAR and TNF-α levels are correlated with peri-implant PD.
Abstract: BACKGROND: One of the important areas of heart research is to analyze heart rate variability during (HRV) walking. OBJECTIVE: In this research, we investigated the correction between heart activation and the variations of walking paths. METHOD: We employed Shannon entropy to analyze how the information content of walking paths affects the information content of HRV. Eight healthy students walked on three designed walking paths with different information contents while we recorded their ECG signals. We computed and analyzed the Shannon entropy of the R-R interval time series (as an indicator of HRV) versus…the Shannon entropy of different walking paths and accordingly evaluated their relation. RESULTS: According to the obtained results, walking on the path that contains more information leads to less information in the R-R time series. CONCLUSION: The analysis method employed in this research can be extended to analyze the relation between other physiological signals (such as brain or muscle reactions) and the walking path.
Keywords: Heart Rate Variability (HRV), walking path, Shannon entropy, information content, R-R interval time series
Abstract: BACKGROUND: Drawing blood from the fingertips for glucose testing is painful and likely to cause tissue damage over time. Earlobes are an alternative site for glucose measurement. OBJECTIVE: This work aims to validate the earlobe as an alternate test site for blood glucose testing by demonstrating valid and reliable statistically significant differences between the earlobes and standard reference sites. METHODS: Blood glucose concentrations from 50 volunteers were measured and statistically analysed from the reference sites (forearm and fingertip) and earlobe. The analysis included: 1) one-way analysis of variance (ANOVA), 2) regression analysis, 3)…Bland Altman analysis, and 4) Clarke Error Grid analysis. RESULTS: The results indicated that there is no statistically significant difference between the three blood glucose-testing methods. For the forearm-earlobe and fingertip-earlobe, all measurements were grouped around the mean of 3.7 ± 1.96 SD and 2.96± 1.96 SD, respectively. Error grid analysis showed > 97% of all earlobe and references measurements fell in Zones A and B and were in the clinically acceptable level. CONCLUSIONS: The results have shown that the earlobe is a valid substitute for blood glucose measurements.
Abstract: BACKGROUND: The results of medical image segmentation can provide reliable evidence for clinical diagnosis and treatment. The U-Net proposed previously has been widely used in the field of medical image segmentation. Its encoder extracts semantic features of different scales at different stages, but does not carry out special processing for semantic features of each scale. OBJECTIVE: To improve the feature expression ability and segmentation performance of U-Net, we proposed a feature supplement and optimization U-Net (FSOU-Net). METHODS: First, we put forward the view that semantic features of different scales should be treated differently.…Based on this view, we classify the semantic features automatically extracted by encoders into two categories: shallow semantic features and deep semantic features. Then, we propose the shallow feature supplement module (SFSM), which obtains fine-grained semantic features through up-sampling to supplement the shallow semantic information. Finally, we propose the deep feature optimization module (DFOM), which uses the expansive convolution of different receptive fields to obtain multi-scale features and then performs multi-scale feature fusion to optimize the deep semantic information. RESULTS: The proposed model is experimented on three medical image segmentation public datasets, and the experimental results prove the correctness of the proposed idea. The segmentation performance of the model is higher than the advanced models for medical image segmentation. Compared with baseline network U-NET, the main index of Dice index is 0.75% higher on the RITE dataset, 2.3% higher on the Kvasir-SEG dataset, and 0.24% higher on the GlaS dataset. CONCLUSIONS: The proposed method can greatly improve the feature representation ability and segmentation performance of the model.
Keywords: Deep learning algorithm, medical image analysis, semantic segmentation, multi-scale, convolutional neural networks
Abstract: BACKGROUND: Lip incompetence resulting from mouth breathing is a common clinical manifestation, while there are no definite indicators of amplitude and intensity of muscle functional training in clinical practice, which leads to unsatisfactory training results. OBJECTIVE: The aim was to quantify the relationship between electromyography (EMG) and force in orbicularis oris muscle, so that the indicators of muscle functional training can be evaluated using EMG signals, so as to improve the training effects. METHODS: The EMG and the force signals of orbicularis oris muscle from 0% to 100% MVC within 5 s in…twelve healthy subjects (six males and six females; age, 25 ± 2 years; mass, 60 ± 15 kg) were recorded simultaneously for three trials. Four EMG features consisting of RMS, WAMP, SampEn and FuzzyEn were analyzed. The regression analyses were performed using first-order and third-order polynomial model. RESULTS: There were high correlations between the four EMG features and muscle force with the two models. The third-order model yielded a higher coefficient of determination (R 2 ) than the linear model (p < 0.001) and the result of FuzzyEn (R 2 : 0.884 ± 0.059) was the highest in the four features. CONCLUSION: The third-order model with FuzzyEn of EMG signals may be used to guide the muscle functional training.
Abstract: BACKGROUND: The similar elastic modulus of resin-matrix ceramics to dentin has resulted in their recent widespread application clinically. Nevertheless, the bacterial environment of oral cavity can degrade the resin composite. OBJECTIVE: The objective was to analyse the effect of S. mutans and its fluoride-resistant strains on the adhesion of three CAD/CAM ceramics. METHODS: S. mutans UA159 (UA) was identified, and its fluoride-resistant strain (FR) was induced. For crack observation, three kinds of CAD/CAM ceramics (IPS Empress, Lava Ultimate and Vita Enamic) were bonded with tooth complex (enamel, dentin and flowable resin) through adhesive.…For micro-tensile test, ceramics were bonded with flowable resin, and cut into strip test pieces. Then specimens were immersed into the UA, FR and the control solution (BHI) separately for 14 d. Ceramic-adhesive interface and adhesive-tooth complex interface were observed and analyzed through electron microscope and stereomicroscope. Micro-tensile test was conducted. RESULTS: Specimens in bacterial solutions had more cracks and comparatively weaker micro-tensile strength than those in BHI. In ceramic-adhesive interface, Lava Ultimate produced the most cracks. In adhesive-tooth complex interface, adhesive-dentin produced the most cracks. Meanwhile, IPS Empress had the strongest micro-tensile strength when bonded with resin. CONCLUSIONS: S. mutans and its fluoride resistant strain can cause cracks in the bonding of ceramics and dental tissue, especially resin-matrix ceramic and dentin, and weaken the bonding strength between ceramics and resin.
Abstract: BACKGROUND: Digital competencies are more and more required in everyday work, and training future healthcare professionals in digital health is highly important. OBJECTIVE: Aim of this study was to assess medical students’ gain of knowledge by participation in a teaching module “Digital Health”, and to evaluate their attitudes towards digital health and its role in medical education. METHODS: Students of the module were asked to complete a questionnaire and a multiple-choice-test before and after completing the classes. Students of the same educational level in different modules served as reference group. RESULTS:…34 students took part (n = 17 “Digital Health group”; n = 17 “reference group”). There was no significant difference in pre-existing knowledge between the groups. After having completed the module, participants reached significantly higher scores, compared to their preexisting knowledge (p < 0.05) and the reference group (p < 0.05). Most students found that digital medicine is not sufficiently represented in undergraduate medical education, but will influence everyday work of physicians in the next five years. CONCLUSIONS: Students showed a high awareness for the impact of digital health on physicians’ work. The results suggest that the format can sufficiently transfer knowledge about digital health. Teaching of digital knowledge and competencies should be firmly implemented into medical education to form digitally competent future doctors.
Keywords: Digital health, Undergraduate Medical Education, digital competencies, medical students, data literacy
Abstract: BACKGROUND: The digital twin concept is the virtual model based on entity design measures, which is used in many enterprises’ virtual workshop design models for workshop production scheduling and optimization. However, in the field of medical rehabilitation, the integration of digital twin technology started late compared to traditional industrial manufacturing. Many current digital models are not well suited for information interaction between patients and devices. OBJECTIVE: In order to address the lack of interaction between patients and devices in the field of medical rehabilitation, this paper proposes an automatic gait data control system (AGDCS) for fully…actuated lower limb exoskeleton digital twinning. This system improves the integration of digital twinning system with the medical rehabilitation field and analyzes the patient’s gait data through simulation experiments. METHODS: The digital twin system was designed in several steps. Firstly, the upper computer function module was designed and developed according to the rehabilitation treatment needs. After that, the combination of exoskeleton robot and software was carried out, and finally the real rehabilitation treatment environment of patients was simulated through experiments. RESULTS: The proposed system was very reliable in the experimental tests of the host computer and exoskeleton robot. In the upper computer test, the patient specific gait can be generated, and the motion of the exoskeleton robot can be observed in real-time. During the walking test of the exoskeleton robot, the exoskeleton robot completed the specified gait. The result verified the superiority and effectiveness of the digital twin system AGDCS in the field of rehabilitation. CONCLUSIONS: The digital twin system proposed in this paper improves the interaction between self-balancing exoskeleton robot and patients, and improves the autonomy and safety of patients in rehabilitation treatment.
Keywords: Digital twin system, walking rehabilitation, lower extremity exoskeleton, robotics
Abstract: BACKGROUND: Cervical histopathology image classification is a crucial indicator in cervical biopsy results. OBJECTIVE: The objective of this study is to identify histopathology images of cervical cancer at an early stage by extracting texture and morphological features for the Support Vector Machine (SVM) classifier. METHODS: We extract three different texture features and one morphological feature of cervical histopathology images: first-order histogram, K-means clustering, Gray Level Co-occurrence Matrix (GLCM) and nucleus feature. The original dataset used in our experiment is obtained from 20 patients diagnosed with cervical cancer, including 135 whole slide images (WSIs).…Given an entire WSI, the patches on its tissue region are extracted randomly. RESULTS: We finally obtain 3,000 patches, including 1,000 normal, 1,000 hysteromyoma and 1,000 cancer images. Among them, 80% of the entire data set is randomly selected as training set and the remaining 20% as test set. The accuracy of SVM classification using first-order histogram, K-means clustering, GLAM and nucleus feature for extracting features are respectively 87.4%, 90.6%, 91.6% and 93.5%. CONCLUSIONS: The classification accuracy of the SVM combining the four features is 96.8%, and the proposed nucleus feature plays a key role in the SVM classification of cervical histopathology images.