Feasibility of predicting functional decline in the elderly through key posture information during sit-to-stand movement.

BACKGROUND: Early detection of functional decline in the elderly in day care centres facilitates timely implementation of preventive and treatment measures. RESEARCH QUESTION: Whether or not a predictive model can be developed by applying image recognition to analyze elderly individuals' posture during the sit-to-stand (STS) manoeuvre. METHODS: We enrolled sixty-six participants (24 males and 42 females) in an observational study design. To estimate posture key point information, we employed a region-based convolutional neural network model and utilized nine key points and their coordinates to calculate seven eigenvalues (X1-X7) that represented the motion curve features during the STS manoeuvre. One-way analysis of variance was performed to evaluate four STS strategies and four types of compensation strategies for three groups with different capacities (college students, community-dwelling elderly, and day care center elderly). Finally, a machine learning predictive model was established. RESULTS: Significant differences (p < 0.05) were observed in all eigenvalues except X2 (momentum transfer phase, p = 0.168) between participant groups; significant differences (p < 0.05) were observed in all eigenvalues except X2 (p = 0.219) and X3 (hip-rising phase, p = 0.286) between STS patterns; significant differences (p < 0.05) were observed in all eigenvalues except X2 (p = 0.842) and X3 (p = 0.074) between compensation strategies. The motion curve eigenvalues of the seven posture key points were used to build a machine learning model with 85% accuracy in capacity detection, 70% accuracy in pattern detection, and 85% accuracy in compensation strategy detection. SIGNIFICANCE: This study preliminarily demonstrates that eigenvalues can be used to detect STS patterns and compensation strategies adopted by individuals with different capacities. Our machine learning model has excellent predictive accuracy and may be used to develop inexpensive and effective systems to help caregivers to continuously monitor STS patterns and compensation strategies of elderly individuals as warning signs of functional decline.

Establishment of Hp(3) calibration system for eye dose monitoring in Taiwan.

In response to the ICRP's amending the occupational exposure limit for the eye lens, the Institute of Nuclear Energy Research (INER) established the Hp(3) calibration system for eye dose monitoring in Taiwan to accurately assess the dose received in the eye lens. INER employed the narrow-spectrum series radiation according to the ISO 4037 as the X-ray radiation qualities, and the measured half-value layer consistent with a 5% difference. The air kerma rate standard was determined by the self-made free air chamber, and through dose conversion coefficient referring to ISO 4037 to obtain the Hp(3) on an ISO cylinder phantom. Furthermore, the calibration system was provided as the characteristics tests for DOSIRIS headset dosemeters. Finally, the Hp(3) calibration system has been established in Taiwan, and it can be used to provide calibration services for eye lens dosemeters and be applied to the proficiency testing that will be held in 2023.

Assessing the sustainability of smart healthcare applications using a multi-perspective fuzzy comprehensive evaluation approach.

A smart healthcare application can be judged as sustainable if it was already widely used before and will also be prevalent in the future. In contrast, if a smart healthcare application developed during the COVID-19 pandemic is not used after it, then it is not sustainable. Assessing the sustainability of smart healthcare applications is a critical task for their users and suppliers. However, it is also a challenging task due to the availability of data, users' subjective beliefs, and different perspectives. In response to this problem, this study proposes a multi-perspective fuzzy comprehensive evaluation approach to evaluate the sustainability of a smart healthcare application from qualitative, multi-criteria decision-making and time-series perspectives. The proposed methodology has been used to evaluate the sustainability of eight smart healthcare applications. The experimental results showed that the sustainability of a smart healthcare application evaluated from different perspectives may be different. Nevertheless, another technique can be used to confirm the evaluation result generated using one technique. In other words, these views compensate for each other.

Evaluating the sustainability of smart technology applications in healthcare after the COVID-19 pandemic: A hybridising subjective and objective fuzzy group decision-making approach with explainable artificial intelligence.

During the COVID-19 pandemic, some smart technology applications were more effective than had been expected, whereas some others did not achieve satisfactory performance. Consequently, whether smart technology applications in healthcare are sustainable is a question that warrants investigation. To address this question, a hybridising subjective and objective fuzzy group decision-making approach with explainable artificial intelligence was proposed in this study and then used to evaluate the sustainability of smart technology applications in healthcare. The contribution of this research is its subjective evaluation of the sustainability of smart technology applications followed by correction of the evaluation outcome on the basis of the applications' objective performance during the COVID-19 pandemic. To this end, a fuzzy nonlinear programming model was formulated and optimised. In addition, the impact of several major global events that occurred during the pandemic on the sustainability of smart technology applications was considered. The proposed methodology was applied to evaluate the sustainability levels of eight smart technology applications in healthcare. According to the experimental results, three applications-namely healthcare apps, smartwatches, and remote temperature scanners-are expected to be highly sustainable in healthcare, whereas one application, namely smart clothing, is not.

A ubiquitous healthcare system of 3D printing facilities for making dentures: Application of type-II fuzzy logic.

A ubiquitous healthcare (UH) system of multiple 3D printing facilities is established in this study for making dentures. The UH system receives orders from dental clinics, and then distributes the dentures to be printed among 3D printing facilities to save time. Compared with existing systems for similar purposes, the UH system has two novel features. The first is the consideration of the possibility of reprinting in formulating the plan to avoid replanning. The other is the cooperation with home delivery services that have gradually become popular during the COVID-19 pandemic to save transportation time. The new features are subject to considerable uncertainties. To account for the uncertainties, both printing time and transportation time are modelled using interval type-II trapezoidal fuzzy numbers. Subsequently, an interval type-II fuzzy mixed integer-linear programming (FMILP) model is formulated and optimized to plan the operations of the UH system. A case study has been conducted to illustrate the applicability of the proposed methodology. According to experimental results, the proposed methodology was able to shorten the order fulfillment time by up to 9%.

Effects of compression garment on muscular efficacy, proprioception, and recovery after exercise-induced muscle fatigue onset for people who exercise regularly.

Fatigue is a major cause of exercise-induced muscle damage (EIMD). Compression garments (CGs) can aid post-exercise recovery, therefore, this study explored the effects of CGs on muscular efficacy, proprioception, and recovery after exercise-induced muscle fatigue in people who exercise regularly. Twelve healthy participants who exercised regularly were enrolled in this study. Each participant completed an exercise-induced muscle fatigue test while wearing a randomly assigned lower-body CG or sports pants (SP); after at least 7 days, the participant repeated the test while wearing the other garment. The dependent variables were muscle efficacy, proprioception (displacements of center of pressure/COP, and absolute error), and fatigue recovery (muscle oxygen saturation/SmO2, deoxygenation and reoxygenation rate, and subjective muscle soreness). A two-way repeated measure analysis of variance was conducted to determine the effect of garment type. The results indicated that relative to SP use, CG use can promote muscle efficacy, proprioception in ML displacement of COP, and fatigue recovery. Higher deoxygenation and reoxygenation rates were observed with CG use than with SP use. For CG use, SmO2 quickly returned to baseline value after 10 min of rest and was maintained at a high level until after 1 h of rest, whereas for SP use, SmO2 increased with time after fatigue onset. ML displacement of COP quickly returned to baseline value after 10 min of rest and subsequently decreased until after 1 hour of rest. Relative to SP use, CG use was associated with a significantly lower ML displacement after 20 min of rest. In conclusion, proprioception and SmO2 recovery was achieved after 10 min of rest; however, at least 24 h may be required for recovery pertaining to muscle efficacy and soreness regardless of CG or SP use.

A Fuzzy Collaborative Intelligence Approach to Group Decision-Making: a Case Study of Post-COVID-19 Restaurant Transformation.

In a fuzzy group decision-making task, when decision makers lack consensus, existing methods either ignore this fact or force a decision maker to modify his/her judgment. However, these actions may be unreasonable. In this study, a fuzzy collaborative intelligence approach that seeks the consensus among experts in a novel way is proposed. Fuzzy collaborative intelligence is the application of biologically inspired fuzzy logic to a group task. The proposed methodology is based on the fact that a decision maker must make a choice even if he/she is uncertain. As a result, the decision maker's fuzzy judgment matrix may not be able to represent his/her judgment. To solve such a problem, the fuzzy judgment matrix of each decision maker is decomposed into several fuzzy judgment submatrices. From the fuzzy judgment submatrices of all decision makers, a consensus can be easily identified. The proposed fuzzy collaborative intelligence approach and several existing methods have been applied to the case of the post-COVID-19 transformation of a Japanese restaurant in Taiwan. Because such transformation was beyond the expectation of the Japanese restaurant, the employees lacked consensus if existing methods were applied to identify their consensus. The proposed methodology solved this problem. The optimal transformation plan involved increasing the distance between tables, erecting screens between tables, and improving air circulation. In a fuzzy group decision-making task, an acceptable decision cannot be made without the consensus among decision makers. Ignoring this or forcing decision makers to modify their preferences is unreasonable. Identifying the consensus among experts from another point of view is a viable treatment.

Assessing the Robustness of a Factory Amid the COVID-19 Pandemic: A Fuzzy Collaborative Intelligence Approach.

The COVID-19 pandemic has affected the operations of factories worldwide. However, the impact of the COVID-19 pandemic on different factories is not the same. In other words, the robustness of factories to the COVID-19 pandemic varies. To explore this topic, this study proposes a fuzzy collaborative intelligence approach to assess the robustness of a factory to the COVID-19 pandemic. In the proposed methodology, first, a number of experts apply a fuzzy collaborative intelligence approach to jointly evaluate the relative priorities of factors that affect the robustness of a factory to the COVID-19 pandemic. Subsequently, based on the evaluated relative priorities, a fuzzy weighted average method is applied to assess the robustness of a factory to the COVID-19 pandemic. The assessment result can be compared with that of another factory using a fuzzy technique for order preference by similarity to ideal solution. The proposed methodology has been applied to assess the robustness of a wafer fabrication factory in Taiwan to the COVID-19 pandemic.

Assessing sustainable effectiveness of the adjustment mechanism of a ubiquitous clinic recommendation system.

Advances in computer and communication technologies have engendered opportunities for developing an improved ubiquitous health care environment. One of the crucial applications is a ubiquitous clinic recommendation system, which entails recommending a suitable clinic to a mobile patient based on his/her location, hospital department, and preferences. However, patients may not be willing or able to express their preferences. To overcome this problem, some ubiquitous clinic recommendation systems mine the historical data of patients to learn their preferences, and they apply an algorithm to adjust the recommendation algorithm after receiving more patient data. Such an adjustment mechanism may operate for several periods; however, this raises a question regarding the sustainability (i.e., long-term effectiveness) of such an adjustment mechanism. To address this question, this study modeled the improvement in the successful recommendation rate of a ubiquitous clinic recommendation system that adopts an adjustment mechanism as a learning process. Both the asymptotic value and learning speed of the learning process provide valuable information regarding the long-term effectiveness of the adjustment mechanism. The proposed methodology was applied in a regional study to a ubiquitous clinic recommendation system that adjusts the recommendation mechanism by solving an integer nonlinear programming problem on a rolling basis. The experimental results revealed that the proposed method exhibited a considerably higher level of accuracy in forecasting the successful recommendation rate compared with several existing methods. Although the adjustment mechanism exhibits long-term effectiveness, the learning speed requires improvement.

Mining the preferences of patients for ubiquitous clinic recommendation.

A challenge facing all ubiquitous clinic recommendation systems is that patients often have difficulty articulating their requirements. To overcome this problem, a ubiquitous clinic recommendation mechanism was designed in this study by mining the clinic preferences of patients. Their preferences were defined using the weights in the ubiquitous clinic recommendation mechanism. An integer nonlinear programming problem was solved to tune the values of the weights on a rolling basis. In addition, since it may take a long time to adjust the values of weights to their asymptotic values, the back propagation network (BPN)-response surface method (RSM) method is applied to estimate the asymptotic values of weights. The proposed methodology was tested in a regional study. Experimental results indicated that the ubiquitous clinic recommendation system outperformed several existing methods in improving the successful recommendation rate.

Gait speed and gender effects on center of pressure progression during normal walking.

The COP progression is the trajectory of the center of foot pressure. Thirty healthy young adults were recruited to participate in this study. All subjects were asked to walk randomly at four different speeds (3km/h, preferred walking speed, 4km/h and 5km/h). A foot pressure measurement system (RS-scan(®) system) was used to collect the center of pressure (COP) coordinates, COP progression angle and the COP velocity. Four sub-phases of the stance phase were calculated. The initial contact (ICP) and forefoot contact phase (FFCP) corresponded to the loading response. The foot flat phase (FFP) coincided with the mid-stance. The forefoot push-off phase (FFPOP) corresponded to the terminal stance and pre-swing phases. The results of this study indicate that the percentage of time (% time) of COP progression on the ICP, FFCP, FFP and FFPOP were approximately 7.0%, 4.8%, 48.8% and 39.4%, respectively. The COP progression angle was 4.1 (SD=1.6)° with an inward curve and the average COP velocity was 31.6cm/s (SD=5.3). The walking speed influenced the % time in the FFP and FFPOP. As the walking speed increased, the % time of COP progression decreased in mid-stance and increased in the terminal and pre-swing stances. Moreover, gender affected the COP progression angle. Men had a significantly larger deviating angle than women during FFCP, FFP and FFPOP. The COP characteristics can offer useful information for clinical rehabilitation in foot functional and structural evaluation.

Center of pressure progression characteristics under the plantar region for elderly adults.

This investigation identifies the center of pressure (COP) progression characteristics under the plantar region for elderly adults during barefoot walking. A total of 60 healthy adults (30 young and 30 old) were recruited. The young and elderly participants had average ages of 23.6 (SD=2.7) and 70.8 (SD=4.1) years old, respectively. All subjects had normal foot arch and no relevant musculoskeletal disease in the lower extremities. The foot pressure measurement system (RS-scan(®) system) was used to measure the center of pressure coordinates (COP), progression angle and COP velocity. Four sub-phases of the stance phase were calculated. The initial contact (ICP) and forefoot contact phase (FFCP) corresponded to the loading response. The foot flat phase (FFP) coincided with the mid-stance. The forefoot push-off phase (FFPOP) corresponded to the terminal stance and pre-swing phases. The analytical results revealed that age effects were found in the relative time percentages for the initial contact, foot flat and forefoot push-off phases during foot movement. The elderly subjects exhibited significant medial COP curve and faster COP velocity during the initial contact phase and more pronated mid-foot posture and slower COP velocity during the mid-stance. The older adults tended to have a more pronated foot and displayed a significant medial COP curve compared to young adults. These COP progression characteristics can provide further insight into relevant foot function and gait performance evaluations for older adults.

Surface and superficial dose dosimetric verification for postmastectomy radiotherapy.

In patients given postmastectomy radiotherapy (PMRT), the chest wall is a very thin layer of soft tissue with a low-density lung tissue behind. Chest wall treated in this situation with a high-energy photon beam presents a high dosimetric uncertainty region for both calculation and measurement. The purpose of this study was to measure and to evaluate the surface and superficial doses for patients requiring PMRT with different treatment techniques. An elliptic cylinder cork and superflab boluses were used to simulate the lung and the chest wall, respectively. Sets of computed tomography (CT) images with different chest wall thicknesses were acquired for the study phantom. Hypothetical clinical target volumes (CTVs) were outlined and modified to fit a margin of 1-3 mm, depending on the chest wall thickness, away from the surface for the sets of CT images. The planning target volume (PTV) was initially created by expanding an isotropic 3-mm margin from the CTV, and then a margin of 3 mm was shrunk from the phantom surface to avoid artifact-driven results in the beam-let intensity. Treatment techniques using a pair of tangential wedged fields (TWFs) and 4-field intensity-modulated radiation therapy (IMRT) were designed with a prescribed fraction dose (D(p)) of 180 cGy. Superficial dose profiles around the phantom circumference at depths of 0, 1, 2, 3, and 5 mm were obtained for each treatment technique using radiochromic external beam therapy (EBT) films. EBT film exhibits good characteristics for dose measurements in the buildup region. Underdoses at the median and lateral regions of the TWF plans were shown. The dose profiles at shallow depths for the TWF plans show a dose buildup about 3 mm at the median and lateral tangential incident regions with a surface dose of about 52% of D(p). The dose was gradually increased toward the most obliquely tangential angle with a maximum dose of about 118% of D(p.) Dose profiles were more uniform in the PTV region for the 4-F IMRT plans. Most of the PTV region had doses >94% of D(p) at depths >1 mm. The mean surface dose was about 65% of D(p) for the 4-F IMRT plans. The maximum dose for the 4-F IMRT plans was <118.4% of D(p). The application of added bolus has to consider the treatment technique, tumor coverage, and possible skin reactions. For PMRT, if the chest surface and wall are treated adequately, at least 3 mm bolus should be added to the chest wall when tangential beams and 6-MV photon energy are arranged. However, when the surface and superficial regions are not high-risk areas, an IMRT plan with tangential beams and 6-MV photon energy can provide uniform dose distributions within the PTV, spare the skin reaction, and deliver sufficient doses to the chest wall at depths >1 mm.

Midline dose verification with diode in vivo dosimetry for external photon therapy of head and neck and pelvis cancers during initial large-field treatments.

During radiotherapy treatments, quality assurance/control is essential, particularly dose delivery to patients. This study was designed to verify midline doses with diode in vivo dosimetry. Dosimetry was studied for 6-MV bilateral fields in head and neck cancer treatments and 10-MV bilateral and anteroposterior/posteroanterior (AP/PA) fields in pelvic cancer treatments. Calibrations with corrections of diodes were performed using plastic water phantoms; 190 and 100 portals were studied for head and neck and pelvis treatments, respectively. Calculations of midline doses were made using the midline transmission, arithmetic mean, and geometric mean algorithms. These midline doses were compared with the treatment planning system target doses for lateral or AP (PA) portals and paired opposed portals. For head and neck treatments, all 3 algorithms were satisfactory, although the geometric mean algorithm was less accurate and more uncertain. For pelvis treatments, the arithmetic mean algorithm seemed unacceptable, whereas the other algorithms were satisfactory. The random error was reduced by using averaged midline doses of paired opposed portals because the asymmetric effect was averaged out. Considering the simplicity of in vivo dosimetry, the arithmetic mean and geometric mean algorithm should be adopted for head/neck and pelvis treatments, respectively.

Evaluating work ability and quality of life for clinical nurses in Taiwan.

This study investigated the work ability and its relationship with quality of life for the clinical nurses in Taiwan. The survey was of 1534 nursing professionals from 8 different hospitals. Work ability of nursing professionals varied by age, work experience, working departments and hospital types. Work ability of nurses increased with age until after the age of 45. Personal health condition and physical workload were the main factors contributing to the decline of the perceived work ability for senior nurses. For young nurses, the mental demands of work were a critical influence on their work ability. Moreover, work ability of nurses varied among hospital type and department. The work ability of nurses was strongly associated with the quality and safety of the work environment and leisure time management. For improving and maintaining the work ability of nurses, countermeasures such as enhancing the ability to cope with the job's mental demands for young nurses, and improving the job design to reduce physical workload for senior nurses are recommended.

The effect of gait speed and gender on perceived exertion, muscle activity, joint motion of lower extremity, ground reaction force and heart rate during normal walking.

This study aims to investigate the effect of speed and gender on subjective perceived exertion, muscle activity, joint motion of lower extremity, vertical ground reaction force and heart rate during barefoot walking. Thirty healthy young adults, 15 females and 15 males, participated in this study. The Borg CR-10 scale was applied to evaluate the perceived exertion of whole body and 10 local areas. Objective measurements included electromyography (EMG), joint motion, vertical ground reaction force (VGRF) and heart rate. The results indicate that walking speed had significant influence on perceived exertion of whole body, as well as the buttock, rear thigh, front thigh and rear shank areas (p<0.05). Increased walking speed caused significant increase in the muscle activities of lumbar erector spinae, biceps femoris, and medial gastrocnemius, lumbar motion, as well as the vertical ground reaction force in the loading response and mid-stance phases. For gender effect, females showed significantly higher tibialis anterior muscle activity, ankle motion, vertical ground reaction force and average heart rate than males. Some systematic relations among the physiological, kinematics, kinetics and psychophysical responses were found for interpreting gait performance.

Professional footwear evaluation for clinical nurses.

Epidemiological investigations indicate that nursing professionals experience a higher prevalence of musculoskeletal disorders (MSDs) than most other occupational groups. Most nursing activities require standing and walking for prolonged periods. Such job requirements may contribute to MSD problems in the lower extremities. Thus, wearing comfortable nursing shoes is essential to reduce the lower-extremity discomfort for clinical nurses. The objectives of this study are: (1) to evaluate three brands of commercially available nursing footwear and identify the important shoe features for adequate shoe support during nursing activities, and (2) to assess the effect of wearing compression hosiery by measuring the biomechanical, physiological, and psychophysical responses of test participants. The method of this study involved two phases. First, field observations were conducted to collect job demand data, including walking speed, and the ratios of walking, standing, and sitting. Second, an experiment was conducted to evaluate the functions of professional nursing footwear and examine the influence of compression hosiery on lower extremity discomfort relief. Measurements included electromyography (EMG) of the lower leg, joint range of motion (ROM) in the lower extremity, foot pressure, ground reaction force (GRF), and subjective discomfort ratings for the lower body and feet. Summarizing the findings of this study, comfortable footwear for nursing professionals should emphasize a footbed with arch support outside with 1.5 cm thickness of EVA materials in the metatarsal zone and heel height between 1.8 and 3.6 cm; this can minimize foot pressure distribution, impact force, and increase shin and ankle comfort. In addition, wearing compression hosiery is recommended to alleviate lower body and foot discomfort for clinical nurses.