Purchase individual online access for 1 year to this journal.
Price: EUR 150.00
Impact Factor 2020: 0.806
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: Brain activity analysis is an important research area in the field of human neuroscience. Moreover, a subcategory in this field is the classification of brain activity in terms of different brain disorders. Since the Electroencephalography (EEG) signal is, in fact, a non-linear time series, employing techniques to investigate its non-linear structure is rather crucial. In this study, we evaluate the non-linear structure of the EEG signal between healthy and schizophrenic adolescents using fractal theory. The results of our analysis revealed that in terms of all recording channels, the EEG signal of healthy subjects is more complex compared to the ones…suffering from schizophrenia. The statistical analysis also indicated that there is a significant difference in the complex structure of the EEG signal between these two groups of subjects. We also utilized approximate entropy in our analysis in order to verify the obtained results of the fractal analysis. The result of the entropy analysis suggested that EEG signal for healthy subjects is less random compared to the EEG signal in schizophrenic individuals. In addition, the employed methodology in this research can be further investigated in order to classify the brain activity in terms of other brain disorders, where one can explore how the complex structure of the EEG signal alters between them.
Keywords: Electroencephalography (EEG) signal, schizophrenia, fractal, complex, approximate entropy, random
Abstract: BACKGROUND: Although actigraphy is widely used to measure sleep quality, few studies directly compared actigraphy data with polysomnography data, especially electromyography data. OBJECTIVE: We developed an algorithm which transforms actigraphy and electromyography signals to verify the interchangeability between them and tested the utility of this algorithm in sleep healthcare. METHODS: Thirty-eight subjects underwent polysomnography and actigraphy. We transformed electromyography signals extracted from polysomnography as integrated electromyography (IEMG) and actigraphy signals as integrated acceleration (IACC) using their physical properties. We compared receiver operating characteristic (ROC) curves obtained from transformed datasets with those of raw…datasets in distinguishing REM and non-REM sleep. RESULTS: There was no significant correlation between raw electromyography and raw actigraphy data (r = 0.001, p = 0.124). After applying our transformation algorithm, significant correlation between IEMG and IACC was shown (r = 0.392, p < 0.001). In order to overcome small adjusted R 2 from simple regression model (adjusted R= 2 0.153, p < 0.001), we used panel data regression model to correct individual variances (adjusted R= 2 0.542, p < 0.001). In ROC curve for distinguishing REM and non-REM sleep, AUCs were 0.536, 0.735 and 0.729 in raw data, IEMG and IACC respectively. CONCLUSIONS: The transformation algorithm revealed the relationship between electromyography and actigraphy data, and also yielded improved sleep staging ability.
Abstract: This paper introduces a comprehensive fetal Electrocardiogram (fECG) Signal Extraction and Analysis Virtual Instrument that integrates various methods for detecting the R-R Intervals (RRIs) as a means to determine the fetal Heart Rate (fHR) and therefore facilitates fetal Heart Rate Variability (HRV) signal analysis. Moreover, it offers the capability to perform advanced morphological fECG signal analysis called ST segment Analysis (STAN) as it seamlessly allows the determination of the T-wave to QRS complex ratio (also called T/QRS) in the fECG signal. The integration of these signal processing and analytical modules could help clinical researchers and practitioners to noninvasively monitor and…detect the life threatening hypoxic conditions that may arise in different stages of pregnancy and more importantly during delivery and could therefore lead to the reduction of unnecessary C-sections. In our experiments we used real recordings from a Fetal Scalp Electrode (FSE) as well as maternal abdominal electrodes. This Virtual Instrument (Toolbox) not only serves as a desirable platform for comparing various fECG extraction signal processing methods, it also provides an effective means to perform STAN and HRV signal analysis based on proven ECG morphological as well as Autonomic Nervous System (ANS) indices to detect hypoxic conditions.
Abstract: BACKGROUND: Screening tools are critical in the early prevention of cervical cancers. Acetic-acid based colposcopy test provides an affordable solution but is often challenged by the lack of experienced doctors in under-developed districts. OBJECTIVE: To evaluate the feasibility of an internet-based expert system to better utilize the expert knowledge. METHODS: A centralized internet-based expert system was developed to upload acetowhite images acquired by an integrated colposcopy device at remote healthcare centers. The detection rates of high grade cervical intraepithelial neoplasia (CIN) during two consecutive years (installed in the second year) were collected at…two study sites and twelve control sites. RESULTS: No difference in the detection rate was observed between study and control sites at baseline (year 1); however, greater detection rates were found at study sites after introducing the internet-based expert system (year 2). Comparing the detection rates at each site between year 1 and year 2, the study site exhibited improved detection rates. User feedbacks suggested “great learning experience from expert feedback” as the most recognized benefits. CONCLUSIONS: This study shows the feasibility of an internet-based expert system in screening cervical cancers and lays the foundation to future population-level application in under-developed districts.
Abstract: Macular diseases, including neovascular age-related macular degeneration (nvAMD), are leading causes of irreversible blindness and visual impairment. One prominent feature of nvAMD is the detachment of the retinal pigment epithelium. The aim of this study is to implement an automated method for the segmentation of the pigment epithelial detachment (PED) using optical coherence tomography (OCT). OCT datasets from 8 patients with nvAMD were acquired during multiple sessions. At each session, 17 images with a resolution of 1020 × 640 pixels were obtained. The images were segmented using Gaussian filtering and template matching for the detection of the upper and lower…border of the PED, respectively. The results of the method were compared with the ones obtained from the manual segmentation of the images by an expert. Four well-known metrics were used to evaluate the performance of the method with respect to the manual segmentation, resulting in high scores of consistency. Furthermore, the proposed method was also compared with four other well-known methods providing similar or superior performance.
Abstract: BACKGROUND: Several studies showed encouraging results after total disc replacement (TDR) in patients with cervical-brachial syndrome (CBS). OBJECTIVE: The aim of this study was to supplement the existing documentation of results after total disc replacement and to underline the importance of the correct indication. METHODS: The clinical and radiological outcome of 34 patients was evaluated in a 2-year follow-up by several parameters as the Visual Analogue Scale (VAS) for pain, the Neck Disability Index (NDI) and the Kellgren and Lawrence Score. RESULTS: The median values for NDI changed from 65%…(20–90) before surgery to 20% (0–86) 2 years after surgery (p < 0.0001). Pain intensity had an average rate of reduction from 8.4 ± 2 cm (VAS scale 0–10 cm) to 2.9 ± 2 cm (p < 0.0001). A median of 1 (0–3) was calculated for the Kellgren and Lawrence Score in the affected segment preoperatively. Due to loosening in five cases the TDR was removed and changed into anterior cervical decompression and fusion (ACDF). In all of these five cases a preoperative Kellgren and Lawrence Score of 2 or 3 was calculated and five of five patients (100%) were smokers. CONCLUSION: The use of TDR in nonsmoking patients with a low preoperative Kellgren and Lawrence Score of 0–1 lead to a clinically and radiologically successful outcome.
Keywords: Cervical brachial syndrome, total disc replacement, cervical spine
Abstract: BACKGROUND: Blood transfusion is a common practice, but it is not without cost and risk. A model that predicts the risk of blood transfusion could guide informed preoperative blood ordering and use of blood loss preventive measures. OBJECTIVE: This study aimed to develop a prediction model of blood transfusion in children with developmental dysplasia of the hip (DDH) undergoing surgery. METHODS: A retrospective cohort of DDH patients from 2008 to 2017. The included patients were between 1 to 9 years old, underwent anterior open reduction and/or acetabular osteotomy with and without femoral shortening.…The unit of analysis was undergoing such an operation. The outcome was allogenic blood transfusion. Potential predictors were age, sex, body mass index (BMI), international hip dysplasia institute grade, type of surgery, intervention bilaterally during the same operative session, primary versus reoperation surgery, the addition of regional anaesthesia, preoperative haemoglobin and hematocrit. RESULTS: A total of 524 patients who met the inclusion criteria underwent 721 operative sessions. The median age (interquartile range) at operation was 23 (20–33) months. The blood transfusion rate was 11.8%. Independent predictors were lower preoperative haemoglobin, reduced BMI, simultaneous bilateral surgery and the extent of surgical treatment. CONCLUSIONS: The developed prognostic model allows prediction for blood transfusion in DDH patients undergoing surgery.
Keywords: Children, hip dislocation, hip dysplasia, blood transfusion, surgery, decision modeling
Abstract: BACKGROUND: As an innovative technique without cable connection, targeted drug-delivery capsules improve diagnostic and therapeutic capabilities in the gastrointestinal (GI) tract. OBJECTIVE: To fast track targeted drug-delivery capsules in the GI tract, a tracking method based on the multiple alternating magnetic sources with adaptive adjustment of the excitation intensity has been investigated. METHODS: The functional prototype of the tracking system has been developed. The tracking model between the magnetic field strength and the capsule’s location has been established, which shows a nonlinear equation group with multiple local extremum. Particularly, an improved back-propagation (BP)…neural network by particle swarm optimization (PSO) is investigated to solve the tracking problem in real time. The PSO is introduced at an early stage to optimize the weights and thresholds of the BP neural network to improve the generalizability and global search ability. Consequently, the Levenberg-Marquardt (LM) algorithm is used as the learning rule to obtain a higher accuracy and convergence rate. RESULTS: The performance on the PSO-BP neural network is experimentally analyzed by comparing it with the standard BP network and the LM-BP network. CONCLUSIONS: The tracking experiments show that the PSO-BP neural network can solve the tracking problem successfully. The PSO-BP network can get the solution faster than iterative search algorithms.