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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: Knowledge of the location of sensor devices is crucial for many medical applications of wireless body area networks, as wearable sensors are designed to monitor vital signs of a patient while the wearer still has the freedom of movement. However, clinicians or patients can misplace the wearable sensors, thereby causing a mismatch between their physical locations and their correct target positions. An error of more than a few centimeters raises the risk of mistreating patients. OBJECTIVE: The present study aims to develop a scheme to calculate and detect the position of wearable sensors without beacon…nodes. METHODS: A new scheme was proposed to verify the location of wearable sensors mounted on the patient’s body by inferring differences in atmospheric air pressure and received signal strength indication measurements from wearable sensors. Extensive two-sample t tests were performed to validate the proposed scheme. RESULTS: The proposed scheme could easily recognize a 30-cm horizontal body range and a 65-cm vertical body range to correctly perform sensor localization and limb identification. CONCLUSIONS: All experiments indicate that the scheme is suitable for identifying wearable sensor positions in an indoor environment.
Keywords: Barometric altimetry, health monitoring system, location verification, medical monitoring, received signal strength indication, wearable wireless sensors, wireless body area network
Abstract: It is known that the symptoms of Parkinson’s disease (PD) progress successively, early and accurate diagnosis of the disease is of great importance, which slows the disease deterioration further and alleviates mental and physical suffering. In this paper, we propose a joint regression and classification scheme for PD diagnosis using baseline multi-modal neuroimaging data. Specifically, we devise a new feature selection method via relational learning in a unified multi-task feature selection model. Three kinds of relationships (e.g., relationships among features, responses, and subjects) are integrated to represent the similarities among features, responses, and subjects. Our proposed method exploits five regression…variables (depression, sleep, olfaction, cognition scores and a clinical label) to jointly select the most discriminative features for clinical scores prediction and class label identification. Extensive experiments are conducted to demonstrate the effectiveness of the proposed method on the Parkinson’s Progression Markers Initiative (PPMI) dataset. Our experimental results demonstrate that multi-modal data can effectively enhance the performance in class label identification compared with single modal data. Our proposed method can greatly improve the performance in clinical scores prediction and outperforms the state-of-art methods as well. The identified brain regions can be recognized for further medical analysis and diagnosis.
Abstract: BACKGROUND: To help doctors decide their treatment from the aspect of mechanical analysis, the work built a computer assisted optimal system for treatment of femoral neck fracture oriented to clinical application. OBJECTIVE: The whole system encompassed the following three parts: Preprocessing module, finite element mechanical analysis module, post processing module. METHODS: Preprocessing module included parametric modeling of bone, parametric modeling of fracture face, parametric modeling of fixed screw and fixed position and input and transmission of model parameters. Finite element mechanical analysis module included grid division, element type setting, material property setting, contact…setting, constraint and load setting, analysis method setting and batch processing operation. Post processing module included extraction and display of batch processing operation results, image generation of batch processing operation, optimal program operation and optimal result display. RESULTS: The system implemented the whole operations from input of fracture parameters to output of the optimal fixed plan according to specific patient real fracture parameter and optimal rules, which demonstrated the effectiveness of the system. CONCLUSIONS: Meanwhile, the system had a friendly interface, simple operation and could improve the system function quickly through modifying single module.
Abstract: BACKGROUND: A lightweight rehabilitation assisting system is required to help the aged and disabled with daily life activities, thereby improving the quality of their lives. OBJECTIVE: This paper discusses the development of a metal-hydride (MH) actuator, with excellent heat transfer performance, for application in a rehabilitative system incorporating an MH module. METHODS: The operating mechanism of MH actuators requires that the mechanical power of the pneumatic actuator only be generated via heat transfer through a Peltier element and the absorption/desorption of a hydrogen-contained MH module. To achieve this aim, a 3D model was…first designed for two MH modules, and a thermal analysis was carried out according to the type of contact with the Peltier elements to fabricate an MH module with improved heat transfer performance. LabVIEW (National Instruments) was used for automatic temperature control of the Peltier element in the MH actuator driving experiment. Zr 0.9 TI 0.1 Cr 0.6 Fe 1.4 , which yields a pressure-composition-temperature (PCT) curve of appropriate pressure and temperature ranges for a rehabilitative system, was selected as the hydrogen-absorbing alloy. RESULTS: In addition, the temperature conditions of the MH actuator driving experiment were restricted by two temperature control ranges (30–40 ∘ C/30–50 ∘ C) of the Peltier element. Within these Peltier element temperature ranges of 30–40 ∘ C and 30–50 ∘ C, results showed that the MH actuator was driven in the ranges of 2–3 atm and 2.5–3.5 atm, respectively. CONCLUSIONS: These findings indicate that the MH actuator proposed in this paper can be utilized to drive a rehabilitative system for elbow and knee joint exoskeletons.
Abstract: To identify the bio-mark genes related to disease with high dimension and low sample size gene expression data, various regression approaches with different regularization methods have been proposed to solve this problem. Nevertheless, high-noises in biological data significantly reduce the performances of methods. The accelerated failure time (AFT) modelwas designed for gene selection and survival time estimation in cancer survival analysis. In this article, we proposed a novel robust sparse accelerated failure time model (RS-AFT) through combining the least absolute deviation (LAD) and Lq regularization. An iterative weighted linear programming algorithm without regularization parameter tuning was proposed…to solve this RS-AFT model. The results of the experiments show our method has better performancebothin gene selection and survival time estimationthan some widely used regularization methods such as lasso, elastic net and SCAD. Hence we thought the RS-AFT model may be a competitive regularization method in cancer survival analysis.
Abstract: BACKGROUND: The prediction and evaluation of pilot workload is a key problem in human factor airworthiness of cockpit. OBJECTIVE: A pilot traffic pattern task was designed in a flight simulation environment in order to carry out the pilot workload prediction and improve the evaluation method. METHODS: The prediction of typical flight subtasks and dynamic workloads (cruise, approach, and landing) were built up based on multiple resource theory, and a favorable validity was achieved by the correlation analysis verification between sensitive physiological data and the predicted value. RESULTS: Statistical analysis indicated…that eye movement indices (fixation frequency, mean fixation time, saccade frequency, mean saccade time, and mean pupil diameter), Electrocardiogram indices (mean normal-to-normal interval and the ratio between low frequency and sum of low frequency and high frequency), and Electrodermal Activity indices (mean tonic and mean phasic) were all sensitive to typical workloads of subjects. CONCLUSION: A multinominal logistic regression model based on combination of physiological indices (fixation frequency, mean normal-to-normal interval, the ratio between low frequency and sum of low frequency and high frequency, and mean tonic) was constructed, and the discriminate accuracy was comparatively ideal with a rate of 84.85%.
Abstract: BACKGROUND AND OBJECTIVE: To examine the human visual performance (wavefront aberration) and subjective questionnaire (SQ) of visual fatigue when viewing 2-D and 3-D movies. METHODS: Thirty healthy adults observed 2-D and 3-D movies on the same television from a 3m distances during 2D, 3D-A (with better 3D glasses), and 3D-B (with poorer 3D glasses) viewing conditions. Visual quality index, including modulation transfer function index (MTFI), higher order aberration root mean square (RMS), vertical coma (VC), horizontal coma (HC) and spherical aberration (SA), were assessed before and after each viewing condition. One-way repeated measures ANOVA was performed to assess…the changes of each test variable before and after movie viewing. RESULTS: Participants watching movies with 3D-B conditions experienced higher change of MTFI, RMS, VC and HC but smaller SQ, compared with 2D and 3D-A (P < 0.05). Additionally, higher MTFI but smaller SQ was found for 3D-A compared with 2D viewing condition (P < 0.05). CONCLUSIONS: While prolonged viewing 2-D and 3-D movies would lead to poorer visual performance, 3-D glasses with better quality can play the major role in reducing visual ability for users. The change of human eye wavefront aberration might be useful for the evaluation of visual fatigue in the future.
Abstract: BACKGROUND: Non-invasive continuous blood pressure monitoring can provide an important reference and guidance for doctors wishing to analyze the physiological and pathological status of patients and to prevent and diagnose cardiovascular diseases in the clinical setting. Therefore, it is very important to explore a more accurate method of non-invasive continuous blood pressure measurement. OBJECTIVE: To address the shortcomings of existing blood pressure measurement models based on pulse wave transit time or pulse wave parameters, a new method of non-invasive continuous blood pressure measurement – the GA-MIV-BP neural network model – is presented. METHOD: The mean…impact value (MIV) method is used to select the factors that greatly influence blood pressure from the extracted pulse wave transit time and pulse wave parameters. These factors are used as inputs, and the actual blood pressure values as outputs, to train the BP neural network model. The individual parameters are then optimized using a genetic algorithm (GA) to establish the GA-MIV-BP neural network model. RESULTS: Bland-Altman consistency analysis indicated that the measured and predicted blood pressure values were consistent and interchangeable. CONCLUSIONS: Therefore, this algorithm is of great significance to promote the clinical application of a non-invasive continuous blood pressure monitoring method.
Keywords: Pulse wave transit time, pulse wave parameters, non-invasive continuous blood pressure measurement, GA-MIV-BP neural network model