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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: This research studies a medical staff scheduling problem, which includes government regulations and hospital regulations (hard constraints) and the medical staff’s preferences (soft constraints). OBJECTIVE: The objective function is to minimize the violations (or dissatisfaction) of medical staff’s preferences. METHODS: This study develops three variants of the three-phase modified bat algorithms (BAs), named BA1, BA2, and BA3, in order to satisfy the hard constraints, minimize the dissatisfaction of the medical staff and balance the workload of the medical staff. To ensure workload balance, this study balances the workload among medical staff without…increasing the objective function values. RESULTS: Based on the numerical results, the BA3 outperforms the BA1, BA2, and particle swarm optimization (PSO). The robustness of the BA1, BA2, and BA3 is verified. Finally, conclusions are drawn, and directions for future research are highlighted. CONCLUSIONS: The framework of this research can be used as a reference for other hospitals seeking to determine their future medical staff schedule.
Keywords: Bat algorithm (BA), medical staff scheduling, nurse scheduling/rostering, medical staff’s preferences, workload balance
Abstract: BACKGROUND: Venous oxygen saturation reflects venous oxygenation status and can be used to assess treatment and prognosis in critically ill patients. A novel method that can measure central venous oxygen saturation (ScvO 2 ) non-invasively may be beneficial and has the potential to change the management routine of critically ill patients. OBJECTIVE: The study aims to evaluate the potential of sublingual venous oxygen saturation (SsvO 2 ) to be used in the estimation of ScvO 2 . METHODS: We have developed two different approaches…to calculate SsvO 2 . In the first one, near-infrared spectroscopy (NIRS) measurements were performed directly on the sublingual veins. In the second approach, NIRS spectra were acquired from the sublingual tissue apart from the sublingual veins, and arterial oxygen saturation was measured using a pulse oximeter on the fingertip. RESULTS: Twenty-six healthy subjects were included in the study. In the first and second approaches, average SsvO 2 values were 75.0% ± 1.8 and 75.8% ± 2.1, respectively. The results of the two different approaches were close to each other and similar to ScvO 2 of healthy persons (> 70%). CONCLUSION: Oxygen saturation of sublingual veins has the potential to be used in intensive care units, non-invasively and in real-time, to estimate ScvO 2 .
Abstract: BACKGROUND: Current Electronic Health Record (EHR) systems are built using different data representation and information models, which makes difficult achieving information exchange. OBJECTIVE: Our aim was to propose a scalable architecture that allows the integration of information from different EHR systems. METHODS: A cloud-based EHR interoperable architecture is proposed through the standardization and integration of patient electronic health records. The data is stored in a cloud repository with high availability features. Stakeholders can retrieve the patient EHR by requesting only to the integrated data repository. The OpenEHR two-level approach is applied according to…the HL7-FHIR standards. We validated our architecture by comparing it with 5 different works (CHISTAR, ARIEN, DIRAYA, LLPHR and INEHRIS) using a set of selected axes and a scoring method. RESULTS: The problem was reduced to a single point of communication between each EHR system and the integrated data repository. By combining cloud computing paradigm with selected health informatics standards, we obtained a generic and scalable architecture that complies 100% with interoperability requisites according to the evaluation framework applied. CONCLUSIONS: The architecture allowed the integration of several EHR systems, adapting them with the use of standards and ensuring the availability thanks to cloud computing features.
Keywords: Electronic health records, Cloud EHR, interoperability, health informatics standards, HL7 FHIR, OpenEHR
Abstract: BACKGROUND: Breast cancer is a major disease causing panic among women worldwide. Since gene mutations are the root cause for cancer development, analyzing gene expressions can give more insights into various phenotype of cancer treatments. Breast Cancer subtype prediction from gene expression data can provide more information for cancer treatment decisions. OBJECTIVE: Gene expressions are complex for analysis due to its high dimensional nature. Machine learning algorithms such as k-Nearest Neighbors, Support Vector Machine (SVM) and Random Forest are used with selection of features for prediction of breast cancer subtypes. Prediction accuracy of the existing methods…are affected due to high dimensional nature of gene expressions. The objective of the work is to propose an efficient algorithm for the prediction of breast cancer subtypes from gene expression. METHODS: For subtype prediction, a novel Hubness Weighted Support Vector machine algorithm (HWSVM) using bad hubness score as a weight measure to handle the outliers in the data has been proposed. Based on the various subtypes, features are projected into seven different feature sets and Ensemble based Hubness Aware Weighted Support Vector Machine (HWSVMEns) is implemented for breast cancer subtype prediction. RESULTS: The proposed algorithms have been compared with the classical SVM and other traditional algorithms such as Random Forest, k-Nearest Neighbor algorithms and also with various gene selection methods. CONCLUSIONS: Experimental results show that the proposed HWSVM outperforms other algorithms in terms of accuracy, precision, recall and F1 score due to the hubness weightage scheme and the ensemble approach. The experiments have shown an average accuracy of 92% across various gene expression datasets.
Keywords: Breast cancer subtypes, high-dimensional data, hubness, gene selection, support vector machine
Abstract: BACKGROUND: Autonomic function can be estimated non-invasively using heart rate variability (HRV). HRV of patients undergoing coronary artery bypass grafting (CABG) is investigated in time-domain and frequency-domain before and after CABG to study the effect of operation on the status of patients. OBJECTIVE: The main purpose of this work is to evaluate the effect of CABG surgery on patients with ischemic heart disease (IHD) before operation, and to monitor the status of patients on day 6 and day 30 after the CABG operation. METHODS: The statistical signal characterization (SSC) technique is used in…this work in order to derive different morphology-based parameters to indirectly describe time-domain and frequency-domain HRV parameters in 24 patients undergoing CABG operation, before the operation (Group 1: G1), 6 days after operation (Group 2: G2) and 30 days after operation (Group 3: G3). The data is obtained from the Sultan Qaboos University Hospital in Oman. RESULTS: The SSC parameters Mean(mt) and Mean(dt) are reduced in all 24 patients and in 23 out of 24 patients in G2 compared to G1 (6-days after operation compared with before operation), respectively. Comparing G3 to G1 the reduction in Mean(mt) and Mean(dt) is noted in 18 of the 24 patients. CONCLUSIONS: The parameters Mean(mt) and Mean(dt) are successful parameters to follow the HRV for patients undergoing CABG surgery. A relation between those SSC parameters and the HRV time-domain and frequency-domain parameters is investigated in this paper to understand the physiological behavior of the patients.
Keywords: HRV, CABG, statistical signal characterization, signal morphology, time-domain, frequency-domain
Abstract: BACKGROUND: Intracranial pressure (ICP) and arterial blood pressure (ABP) are related to each other through cerebral autoregulation. Central venous pressure (CVP) is often measured to estimate cardiac filling pressures as an approximate measure for the volume status of a patient. Prior modelling efforts have formalized the functional relationship between CVP, ICP and ABP. However, these models were used to explain short segments of data during controlled experiments and have not yet been used to explain the slowly evolving ICP increase that occurs typically in patients after aneurysmal subarachnoid hemorrhage (SAH). OBJECTIVE: To analyze the functional relationship…between ICP, ABP and CVP recorded from SAH patients in the first five days after aneurysm. METHODS: Two methods were used to elucidate this relationship on the running average of the signals: First, using Spearman correlation coefficients calculated over 30 min segments Second, for each patient, linear state space models of ICP as the output and ABP and CVP as inputs were estimated. RESULTS: The mean and variance of the data and the correlation coefficients between ICP-ABP and ICP-CVP vary over time as the patient progresses through their stay in the ICU. On average, after an SAH event, the models show that a) ABP is the bigger driver of changes in ICP than CVP and that increasing ABP leads to reduction in ICP and (b) increasing CVP leads to an increase in ICP. CONCLUSIONS: Finding a) agrees with the hypothesis that patients with subarachnoid hemorrhage have defective autoregulation, and b) agrees with the positive correlation observed between central venous pressure and intracranial pressure in the literature.
Keywords: Intracranial pressure, arterial blood pressure, central venous pressure, relationship, correlation, state space models
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: 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.
Abstract: BACKGROUND: The early detection of human breast cancer represents a great chance of survival. Malignant tissues have more water content and higher electrolytes concentration while they have lower fat content than the normal. These cancer biochemical characters provide malignant tissue with high electric permittivity (ε ´ ) and conductivity (σ ). OBJECTIVE: To examine if the dielectric behavior of normal and malignant tissues at low frequencies (α dispersion) will lead to the threshold (separating) line between them and find the threshold values of capacitance and resistance. These data…are used as input for deep learning neural networks, and the outcomes are normal or malignant. METHODS: ε ´ and σ in the range of 50 Hz to 100 KHz for 15 human malignant tissues and their corresponding normal ones have been measured. The separating line equation between the two classes is found by mathematical calculations and verified via support vector machine (SVM). Normal range and the threshold value of both normal capacitance and resistance are calculated. RESULTS: Deep learning analysis has an accuracy of 91.7%, 85.7% sensitivity, and 100% specificity for instant and automatic prediction of the type of breast tissue, either normal or malignant. CONCLUSIONS: These data can be used in both cancer diagnosis and prognosis follow-up.
Keywords: Breast cancer, dielectric properties, deep learning neural network, α dispersion
Abstract: BACKGROUND: Increased cognitive workload, sometimes known as mental strain or mental effort, has been associated with reduced performance. OBJECTIVE: The use of physiological monitoring was investigated to predict cognitive workload and performance. METHODS: Twenty-one participants completed a 10-minute seated rest, a visuospatial learning task modeled after crane operation, and the Stroop test, an assessment that measures cognitive interference. Heart rate, heart rate variability, electrodermal activity, skin temperature, and electromyographic activity were collected. RESULTS: It was found that participants’ ability to learn the simulated crane operation task was inversely correlated with…self-reported frustration. Significant changes were also found in physiological metrics in the simulation with respect to rest, including an increase in heart rate, electrodermal activity, and trapezius muscle activity; heart rate and muscle activity were also correlated with simulation performance. The relationship between physiological measures and self-reported workload was modeled and it was found that muscle activity and high frequency power, a measure of heart rate variability, were significantly associated with the workload reported. CONCLUSIONS: The findings support the use of physiological monitoring to inform real time decision making (e.g., identifying individuals at risk of injury) or training decisions (e.g., by identifying individuals that may benefit from additional training even when no errors are observed).
Keywords: Cognitive workload, visuospatial learning, wearable sensors, physiological monitoring, health and wellbeing
Abstract: BACKGROUND: Analysis of the heart activity is one of the important areas of research in biomedical science and engineering. For this purpose, scientists analyze the activity of the heart in various conditions. Since the brain controls the heart’s activity, a relationship should exist among their activities. OBJECTIVE: In this research, for the first time the coupling between heart and brain activities was analyzed by information-based analysis. METHODS: Considering Shannon entropy as the indicator of the information of a system, we recorded electroencephalogram (EEG) and electrocardiogram (ECG) signals of 13 participants (7 M, 6…F, 18–22 years old) in different external stimulations (using pineapple, banana, vanilla, and lemon flavors as olfactory stimuli) and evaluated how the information of EEG signals and R-R time series (as heart rate variability (HRV)) are linked. RESULTS: The results indicate that the changes in the information of the R-R time series and EEG signals are strongly correlated (ρ = - 0.9566). CONCLUSION: We conclude that heart and brain activities are related.
Abstract: BACKGROUND: Conventional ultrasound (US) is the most widely used imaging test for thyroid nodule surveillance. OBJECTIVE: We used the color-coded virtual touch tissue imaging (VTI) in the Acoustic Radiation Force Impulse (ARFI) technique to assess the hardness of the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) TR3-5 nodules. The ability of color-coded VTI (CV) to discriminate between benign and malignant nodules was investigated. METHODS: In this retrospective study, US and CV were performed on 211 TR3-5 thyroid lesions in 181 consecutive patients. All nodules were operated on to…obtain pathological results. A multivariate logistic regression model was chosen to integrate the data obtained from the US and CV. RESULTS: The area under the receiver operating characteristic (ROC) curve for the model was 0.945 (95% CI, 0.914 to 0.976). The cutoff value of predictive probability for diagnosing malignant thyroid nodules was 10.64%, the sensitivity was 94.43%, and the specificity was 83.12%. Through comparing with US and CV, respectively, it had been observed that the regression model had the best performance (all P < 0.001). However, when the US was compared with CV, the difference was not significant (P = 0.3304). CONCLUSIONS: A combination of US and CV should be recommended for suspected malignant thyroid nodules in clinical practice.
Abstract: BACKGROUND: Thermoablation is an attractive treatment of thyroid nodules for its minimal-invasiveness. It remains unclear whether results and morbidity meet the patients’ expectations. OBJECTIVE: The aim of the presented study is to show data obtained after microwave thyroid ablation from a patients’ perspective. METHODS: Indications and preoperative diagnosis were chosen according to international guidelines. Thermoablation was achieved using a CE certified microwave system. The procedures heeded the published recommendations of the European Federation of Societies for Ultrasound in Medicine and Biology. Follow-up included ultrasound, laboratory parameters and a standardized questionnaire. RESULTS:…Thirty patients were enrolled into the study. All patients reported an improvement of complaints following the procedure. Scar formation occurred in 3 cases (10%) with 0.5 ± 1.3 mm length and 0.4 ± 1.0 mm width. No cosmetic, neurological, vocal or pharyngeal complication occurred. Energy required for non-functioning nodules (n = 15, 50%) was 2.56 ± 3.41 kJ/mL, for autonomous adenoma (n = 8, 27%) 0.96 kJ/mL (p < 0.05, t -test). CONCLUSION: The presented data summarize an initial experience in selected patients and resemble excellent patient reported outcome with minimal morbidity. These preliminary data indicate the majority of patients satisfied with the procedure. Further trials will be required to endorse these findings.
Keywords: Thyroid ablation, thermoablation of thyroid nodules, microwave thyroid ablation
Abstract: BACKGROUND: Essential tremor (ET) and the tremor in Parkinson’s disease (PD) are the two most common pathological tremors with a certain overlap in the clinical presentation. OBJECTIVE: The main purpose of this work is to use an artificial neural network to select the best features and to discriminate between the two types of tremors. The features used are of hybrid type obtained from two different algorithms: the statistical signal characterization (SSC) of the signal describing its morphology, and the soft-decision wavelet-decomposition (SDWD) features extracted from the accelerometer and surface EMG signals. METHODS: The…SSC method is used to obtain morphology-based features of the spectrum of the accelerometer and two surface EMG signals. The SDWD technique is used in this work to obtain the approximate spectral representation of both accelerometer and the two surface EMG signals. Two sets of data (training and test) are used in this paper. The training set consists of 21 ET subjects and 19 PD subjects, while the test set consists of 20 ET and 20 PD subjects. A neural network of the type feed forward back propagation has been used to combine best SSC features and best SDWD features of the accelerometer and EMG signals. RESULTS: Efficiency result of 92.5% was obtained using best hybrid features. CONCLUSIONS: The artificial neural network has been used successfully to combine two types of features in an automatic discrimination system between PD and ET.
Keywords: Artificial neural networks, statistical signal characterization, wavelet-decomposition, hybrid features, discrimination, PD, ET, accelerometer, EMG
Abstract: BACKGROUND: Severe acetabular bone loss in revision total hip arthroplasty (RTHA), both with or without pelvic discontinuity, remains a great challenge in orthopaedic surgery. OBJECTIVE: The aim of this study was to evaluate risk factors for failure of custom-made acetabular implants in RTHA. METHODS: Seventy patients with severe acetabular bone loss (Paprosky Type III) and pelvic discontinuity, who required RTHA, were included in our study. All prostheses were constructed based on a thin-layer computed-tomography (CT) scan of the pelvis. The treatment was considered unsuccessful in the event of periprosthetic joint infection (PJI) or…aseptic loosening (AL) with need for explantation of the custom-made acetabular implant. RESULTS: The average follow-up was 41.9 ± 34.8 months (range 1.5–120). Implant survival at last follow-up was 75.7% (53 of 70). Explantation was necessary in 17 cases (15 PJI; 2 AL). Previous PJI as reason for RTHA (p = 0.025; OR 3.56 (95% CI: 1.14; 11.21)), additional revision of femoral components (p = 0.003; OR 8.4 (95% CI: 1.75; 40.42)), rheumatoid disease (p = 0.039; OR 3.43 (95% CI: 1.01; 11.40)), elevated preoperative CRP > 15.2 mg/l (p = 0.015; AUC: 0.7) and preoperative haemoglobin < 10.05 (p = 0.022; AUC: 0.69) were statistically significant risk factors associated with treatment failure. Age and BMI were not statistically significant contributing to implant failure. CONCLUSION: Risk factors for treatment failure were a previous PJI, additional revision of femoral component, rheumatoid disease, elevated preoperative CRP and low preoperative haemoglobin. Awareness of these risk factors will help to improve future treatment standards.
Keywords: Revision total hip arthroplasty, pelvic discontinuity, acetabular bone loss, custom-made implant, risk factor, treatment failure, periprosthetic joint infection, aseptic loosening
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. OBJECTIVE: To test the reliability of surface electromyography signals from both the Flexor Digitorum Superficialis (FDS) and Extensor Carpi Radialis Brevis (ECRB) muscles of both the left and right arms during an individual, static multi-planar maximum voluntary contraction handgrip task using the Myon 320 system (Myon AG, Switzerland). METHODS: Eight right-handed male participants performed two maximal handgrip tests in five separate wrist positions using both…hands. Muscle activity was recorded from both forearms. Reliability was measured using the Standard Error of Measurement (SEM), Coefficient of Variation (CV) and Intra-class correlation coefficients. Wrist joint position correlations within and between the FDS and ECRB muscle activities were also analysed. RESULTS: Absolute reliability was shown across all positions for both hands with CV and SEM recorded at below 10%. The output measures indicate that the Myon 320 system (Myon AG, Switzerland) produces good to fair reliability when assessing forearm muscle activity. Correlations in the left FDS muscles were negative. Correlations between the left ECRB and left FDS muscles were variable but positive between the right ECRB and right FDS muscles. CONCLUSIONS: The data sets retrieved from all participants were reliably evaluated. Wrist position correlations within and between the FDS and ECRB muscles may have been influenced by hand dominance. The findings demonstrate that the methods and systems outlined in this study can be used reliably in future research.
Abstract: BACKGROUND: Lesions of articular cartilage represent a crucial risk factor for the early development of osteoarthritis. Autologous chondrocyte implantation (ACI) is a well-established procedure in therapy of those lesions in the knee. The aim of the presented study is to detect differences in short-term radiological outcome depending on defect localization (femoral condyle vs. retropatellar) after spheroid-based ACI. OBJECTIVE: This study aimed to demonstrate that radiological outcome after spheroid-based ACI in the knee is independent of defect localization. METHODS: MRI-scans after retropatellar ACI and ACI of the medial/lateral femoral condyle, with a preoperative Outerbridge…grade of III or IV were evaluated regarding MOCART 2.0. RESULTS: The mean defect-size was 5.0 ± 1.8 cm 2 , with a minimum size of 2 cm 2 and a maximum size of 9 cm 2 . Scans were performed 7.7 months (± 3.1 months) postoperatively. The mean MOCART 2.0 score was 78.5 ± 15.6. No statistically significant influence neither of the localization (p = 0.159), the gender (p = 0.124) nor defect size (< 5 cm 2 vs. ⩾ 5 cm 2 ; p = 0.201) could be observed. CONCLUSIONS: The presented data demonstrate good to excellent radiological short-term results after spheroid-based ACI. Data indicates, that at least radiological results are independent of gender, defect-size and defect-localization.
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: Wearable lower extremity exoskeletons can provide walking assistance for the physical rehabilitation of paralyzed individuals. However, most of the existing exoskeletons require crutches to maintain balance, thus a self-balancing type is needed to improve applicability. OBJECTIVE: The purpose of this work is to study the kinematic characteristics of a novel lower extremity exoskeleton for crutch-less walking rehabilitation, and evaluate the movement performance through practical experiments. METHODS: Based on the human lower limb structure and movement characteristics, a fully actuated 10 degrees-of-freedom (DoF) lower extremity exoskeleton was proposed. The kinematic characteristics of the…exoskeleton were analyzed by the D-H method and geometric method, and the model validity was verified through simulations and experiments. RESULTS: The closed-form solutions for both forward and inverse kinematics models were obtained. The consistent results of theoretical calculation and numerical simulation have shown the accuracy of the established models. The practical experiments regarding six trials have demonstrated the movement performance of the proposed exoskeleton, including sit, stance, leg extension/flexion, and left/right swing. CONCLUSIONS: The kinematic characteristics of the proposed 10-DoF lower extremity exoskeleton are similar to the human lower limb, and it could meet the motion demands of crutch-less walking rehabilitation.
Abstract: BACKGROUND: Optoelectronic systems and force platforms represent the gold standard for postural sway assessment, but pose disadvantages in terms of equipment, cost and preparation time. OBJECTIVE: Wearable inertial measurement units (IMUs) have been proposed to overcome these issues, but have never been compared to an optoelectronic system. The study aim was therefore to investigate agreement between inertial measurement unit and optoelectronic system in postural sway assessment. METHODS: Thirty healthy volunteers performed four balance tasks. IMU was placed on the sacrum (S2) with a retroreflective marker over the sensor and subjects’ performance was simultaneously…recorded by both systems. Total (TOT), anterior-posterior (AP) and medial-lateral (ML) length of trace, range, speed, root mean squared (RMS), and confidence ellipse were computed. RESULTS: ICCs revealed excellent correlations for Length-TOT, Length-AP and Speed-AP, good correlation for Length-ML, Speed-ML, Confidence Ellipse, Range-AP and RMS-AP, and moderate correlation for range-ML and RMS-ML. Bland-Altman plot showed greater estimation for Length-TOT, Length-AP, Speed-AP, confidence ellipse and RMS-AP using optoelectronic system, and for Length-ML, Range-AP, Range-ML, Speed-ML, RMS-ML using IMU. Both systems revealed the same differences among tasks. CONCLUSION: The excellent to good agreement of IMU for length of trace and speed parameters and its user-friendly application suggest its potential implementations in clinical practice.
Keywords: Optoelectronic system, Inertial Measurement Unit, postural sway