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Background: Transitional medication safety is crucial, as miscommunication about medication changes can lead to significant risks. Unclear or incomplete documentation during care transitions can result in outdated or incorrect medication lists at discharge, potentially causing medication errors, adverse drug events, and inadequate patient education. These issues are exacerbated by extended hospital stays and multiple care events, making accurate medication recall challenging at discharge. Objective: Thus, we aimed to investigate how real-time documentation of in-hospital medication changes prevents undocumented medication changes at discharge and improves physician-pharmacist communication. Methods: We conducted a retrospective cohort study in a tertiary hospital. Two pharmacists reviewed medical records of patients admitted to the acute medical unit from April to June 2020. In-hospital medication discrepancies were determined by comparing preadmission and hospitalization medication lists and it was verified whether the physician's intent of medication changes was clarified by documentation. By a documentation rate of medication changes of 100% and <100%, respectively, fully documented (FD) and partially documented (PD) groups were defined. Any undocumented medication changes at discharge were considered a "documentation error at discharge". Pharmacists' survey was conducted to assess the impact of appropriate documentation on the pharmacists. Results: After reviewing 400 medication records, patients were categorized into FD (61.3%) and PD (38.8%) groups. Documentation errors at discharge were significantly higher in the PD than in the FD group. Factors associated with documentation errors at discharge included belonging to the PD group, discharge from a non-hospitalist-managed ward, and having three or more intentional discrepancies. Pharmacists showed favorable attitudes towards physician's documentation. Conclusion: Appropriate documentation of in-hospital medication changes, facilitated by free-text communication, significantly decreased documentation errors at discharge. This analysis underlines the importance of communication between pharmacists and hospitalists in improving patient safety during transitions of care.
During transitions of care, communication failures among healthcare professionals can lead to medication errors. Therefore, effective sharing of information is essential, especially when intentional changes in prescription orders are made. Documenting medication changes facilitates real-time communication, potentially improving medication reconciliation and reducing discrepancies. However, inadequate documentation of medication changes is common in clinical practice. This retrospective cohort study underlines the importance of real-time documentation of in-hospital medication changes. There was a significant reduction in documentation errors at discharge in fully documented group, where real-time documentation of medication changes was more prevalent. Pharmacists showed favorable attitudes toward the physician's real-time documenting of medication changes because it provided valuable information on understanding the physician's intent and improving communication and also saved time for pharmacists. This study concludes that physicians' documentation on medication changes may reduce documentation errors at discharge, meaning that proper documentation of medication changes could enhance patient safety through effective communication.
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PURPOSE: We investigated the influence of passive arm-support exoskeleton (ASE) with different levels of torque (50, 75, and 100%) on upper arm osteokinematics. METHODS: Twenty participants completed a cyclic overhead drilling task with and without ASE. Task duration, joint angles, and angular acceleration peaks were analyzed during ascent and descent phases of the dominant upper arm. RESULTS: Maximum ASE torque was associated with decreased peak acceleration during ascent (32.2%; SD 17.8; p < 0.001) and descent phases (38.8%; SD 17.8; p < 0.001). Task duration remained consistent. Increased torque led to a more flexed (7.2°; SD 5.5; p > 0.001) and internally rotated arm posture (17.6°; SD 12.1; p < 0.001), with minimal changes in arm abduction. CONCLUSION: The small arm accelerations and changes in osteokinematics we observed, support the use of this ASE, even while performing overhead cyclic tasks with the highest level of support.
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We assessed the effects of a passive, back-support exoskeleton (BSE) on lower-limb joint kinetics during the initiation and swing phases of recovery from a forward loss of balance. Sixteen (8M, 8F) young, healthy participants were released from static forward-leaning postures and attempted to recover their balance with a single-step while wearing a BSE (backXTM) with different levels of support torque and in a control condition. The BSE provided â¼ 15-20 Nm of external hip extension torque on the stepping leg at the end of initiation and beginning of swing phases. Participants were unable to generate sufficient hip flexion torque, power, and work to counteract this external torque, although they sustained hip flexion torque for a more prolonged period, resulting in slightly increased hip contribution to positive leg work (compared to control). However, net positive leg work, and the net contribution of hip joint (human + BSE) to total leg work decreased with BSE use. While all participants had changes in hip joint kinetics, a significant compensatory increase in ankle contribution to positive leg work was observed only among females. Our results suggest that BSE use adversely affects reactive stepping by decreasing the stepping leg kinetic energy for forward propulsion, and that the relative contributions of lower-limb joints to total mechanical work done during balance recovery are altered by BSE use. BSEs may thus need to be implemented with caution for dynamic tasks in occupational settings, as they may impair balance recovery following a forward loss of balance.
Subject(s)
Exoskeleton Device , Female , Humans , Knee Joint , Lower Extremity , Hip Joint , Ankle , Biomechanical PhenomenaABSTRACT
BACKGROUND: Measurement of sodium intake in hospitalized patients is critical for their care. In this study, artificial intelligence (AI)-based imaging was performed to determine sodium intake in these patients. OBJECTIVE: The applicability of a diet management system was evaluated using AI-based imaging to assess the sodium content of diets prescribed for hospitalized patients. METHODS: Based on the information on the already investigated nutrients and quantity of food, consumed sodium was analyzed through photographs obtained before and after a meal. We used a hybrid model that first leveraged the capabilities of the You Only Look Once, version 4 (YOLOv4) architecture for the detection of food and dish areas in images. Following this initial detection, 2 distinct approaches were adopted for further classification: a custom ResNet-101 model and a hyperspectral imaging-based technique. These methodologies focused on accurate classification and estimation of the food quantity and sodium amount, respectively. The 24-hour urine sodium (UNa) value was measured as a reference for evaluating the sodium intake. RESULTS: Results were analyzed using complete data from 25 participants out of the total 54 enrolled individuals. The median sodium intake calculated by the AI algorithm (AI-Na) was determined to be 2022.7 mg per day/person (adjusted by administered fluids). A significant correlation was observed between AI-Na and 24-hour UNa, while there was a notable disparity between them. A regression analysis, considering patient characteristics (eg, gender, age, renal function, the use of diuretics, and administered fluids) yielded a formula accounting for the interaction between AI-Na and 24-hour UNa. Consequently, it was concluded that AI-Na holds clinical significance in estimating salt intake for hospitalized patients using images without the need for 24-hour UNa measurements. The degree of correlation between AI-Na and 24-hour UNa was found to vary depending on the use of diuretics. CONCLUSIONS: This study highlights the potential of AI-based imaging for determining sodium intake in hospitalized patients.
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OCCUPATIONAL APPLICATIONSIndustrial robots have become an important aspect in modern industry. In the context of human-robot collaboration, enabling teleoperated robots to work in close proximity to local/onsite humans can provide new opportunities to improve human engagement in a distributed workplace. Interviews with industry stakeholders highlighted several potential benefits of such teleoperator-robot-human collaboration (tRHC), including the application of tRHC to tasks requiring both expertise and manual dexterity (e.g., maintenance and highly skilled tasks in sectors including construction, manufacturing, and healthcare), as well as opportunities to expand job accessibility for individuals with disabilities and older individuals. However, interviewees also indicated potential challenges of tRHC, particularly related to human perception (e.g., perceiving remote environments), safety, and trust. Given these challenges, and the current limited information on the practical value and implementation of tRHC, we propose several future research directions, with a focus on human factors and ergonomics, to help realize the potential benefits of tRHC.
Background The increasing prevalence of robots in industrial environments is attributed in part to advancements in collaborative robot technologies, enabling robots to work in close proximity to humans. Simultaneously, the rise of teleoperation, involving remote robot control, poses unique opportunities and challenges for human-robot collaboration (HRC) in diverse and distributed workspaces.Purpose There is not yet a comprehensive understanding of HRC in teleoperation, specifically focusing on collaborations involving the teleoperator, the robot, and the local or onsite workers in industrial settings, here referred to as teleoperator-robot-human collaboration (tRHC). We aimed to identify opportunities, challenges, and potential applications of tRHC through insights provided from industry stakeholders, thereby supporting effective future industrial implementations.Methods Thirteen stakeholders in robotics, specializing in different domains (i.e., safety, robot manufacturing, aerospace/automotive manufacturing, and supply chains), completed semi-structured interviews that focused on exploring diverse aspects relevant to tRHC. The interviews were then transcribed and thematic analysis was applied to group responses into broader categories, which were further compared across stakeholder industries.Results We identified three main categories and 13 themes from the interviews. These categories include Benefits, Concerns, and Technical Challenges. Interviewees highlighted accessibility, ergonomics, flexibility, safety, time & cost saving, and trust as benefits of tRHC. Concerns raised encompassed safety, standards, trust, and workplace optimization. Technical challenges consisted of critical issues such as communication time delays, the need for high dexterity in robot manipulators, the importance of establishing shared situational awareness among all agents, and the potential of augmented and virtual reality in providing immersive control interfaces.Conclusions Despite important challenges, tRHC could offer unique benefits, facilitating seamless collaboration among the teleoperator, teleoperated robot(s), and onsite workers across physical and geographic boundaries. To realize such benefits and address the challenges, we propose several research directions to further explore and develop tRHC capabilities.
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Ergonomics , Robotics , Robotics/methods , Humans , Ergonomics/methods , Manufacturing Industry/methods , Man-Machine Systems , Research PersonnelABSTRACT
BACKGROUND: The importance of digital technology is increasing among older adults. In this study, the digital health technology utilization status, purpose, and satisfaction of older adults were investigated according to frailty. METHODS: A face-to-face survey was conducted among adults aged 65 years or older. Frailty was defined using the Korean version of the fatigue, resistance, ambulation, illnesses, and loss of weight scale. RESULTS: A total of 505 participants completed the survey, with 153 (30.3%) identified as pre-frail or frail and 352 (69.7%) as healthy. All respondents used smartphones; 440 (87.1%) were application users, and 290 (57.4%) were healthcare application users. Wearable devices were used by only 36 patients (7.1%). Pre-frail or frail respondents used social media more frequently than healthy respondents (19.4% vs. 7.4%, P < 0.001). Among the respondents, 319 (63.2%) were not able to install or delete the application themselves, and 277 (54.9%) stated that the application was recommended by their children (or partner). Pre-frail and frail respondents used more healthcare applications to obtain health information (P = 0.002) and were less satisfied with wearable devices (P = 0.02). CONCLUSION: The usage rate of digital devices, including mobile phones among older adults in Korea is high, whereas that of wearable devices is low. There was a notable difference in the services used by pre-frail and frail respondents compared to healthy respondents. Therefore, when developing digital devices for pre-frail and frail older adults, it is crucial to incorporate customized services that meet their unique needs, particularly those services that they frequently use.
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Digital Health , Frailty , Child , Humans , Aged , Personal Satisfaction , Technology , Republic of KoreaABSTRACT
Exoskeletons (EXOs) are a promising wearable intervention to reduce work-related musculoskeletal disorder risks among construction workers. However, the adoption of EXOs may differ with demographic characteristics. Survey data (n = 361) were collected from construction industry stakeholders and a summation score method was used to summarize respondent's benefits and barriers to EXO use, along with perceptions and readiness to use. Responses were stratified by race (White vs. non-White), sex (male vs. female), and age (<47 years vs. ≥47 years). Both a higher Benefits score and a higher Perceptions score were significantly and positively associated with a higher Readiness to Use score. There were also significant differences in perceived barriers to EXO use by race and sex. These results demonstrate substantial interest in EXO use but also emphasize the need to ensure proportionate access to the potential benefits of EXO technology.
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Construction Industry , Exoskeleton Device , Musculoskeletal Diseases , Humans , Male , Female , Middle Aged , Surveys and Questionnaires , Musculoskeletal Diseases/prevention & control , DemographyABSTRACT
Work-related musculoskeletal disorders (WMSDs) are a major health concern in the construction industry. Occupational exoskeletons (EXOs) are a promising ergonomic intervention to help reduce WMSD risk. Their adoption, however, has been low in construction. To understand the contributing factors to EXO use-intention and assist in future decision-making, we built decision trees to predict responses to each of three EXO use-intention questions (Try, Voluntary Use, and Behavioural Intention), using online survey responses. Variable selection and hyperparameter tuning were used respectively to reduce the number of potential predictors and improve prediction performance. The importance of variables in each final tree was calculated to understand which variables had a greater influence. The final trees had moderate prediction performance. The root node of each tree included EXOs becoming standard equipment, fatigue reduction, or performance increase. Important variables were found to be quite specific to different decision trees. Practical implications of the findings are discussed.Practitioner summary: This study used decision trees to identify key factors influencing the use-intention of occupational exoskeletons (EXOs) in construction, using online survey data. Key factors identified included EXOs becoming standard equipment, fatigue reduction, and performance improvement. Final trees provide intuitive visual representations of the decision-making process for workers to use EXOs.
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BACKGROUND: The hospitalist system has been introduced to improve the quality and safety of inpatient care. As its effectiveness has been confirmed in previous studies, the hospitalist system is spreading in various fields. However, few studies have investigated the feasibility and value of hospitalist-led care of patients with cancer in terms of quality and safety measures. This study aimed to evaluate the efficacy of the Hospitalist-Oncologist co-ManagemEnt (HOME) system. METHODS: Between January 1, 2019, and January 31, 2021, we analyzed 591 admissions before and 1068 admissions after the introduction of HOME system on January 1, 2020. We compared the length of stay and the types and frequencies of safety events between the conventional system and the HOME system, retrospectively. We also investigate rapid response system activation, cardiopulmonary resuscitation, unplanned intensive care unit transfer, all-cause in-hospital mortality, and 30-day re-admission or emergency department visits. RESULTS: The average length of stay (15.9 days vs. 12.9 days, P < 0.001), frequency of safety events (5.6% vs. 2.8%, P = 0.006), rapid response system activation (7.3% vs. 2.2%, P < 0.001) were significantly reduced after the HOME system introduction. However, there was no statistical difference in frequencies of cardiopulomonary resuscitation and intensive care unit transfer, all-cause in-hospital morality, 30-day unplanned re-admission or emergency department visits. CONCLUSIONS: The study suggests that the HOME system provides higher quality of care and safer environment compared to conventional oncologist-led team-based care, and the efficiency of the medical delivery system could be increased by reducing the hospitalization period without increase in 30-day unplanned re-admission.
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Hospitalists , Neoplasms , Humans , Length of Stay , Patient Readmission , Retrospective Studies , Hospitalization , Neoplasms/therapyABSTRACT
Introduction: Wearable I robots such as exoskeletons combine the strength and precision of intelligent machines with the adaptability and creativity of human beings. Exoskeletons are unique in that humans interact with the technologies on both a physical and cognitive level, and as such, involve a complex, interdependent relationship between humans and robots. The aim of this paper was to explore the concepts of agency and adaptation as they relate to human-machine synchrony, as human users learned to operate a complex whole-body powered exoskeleton. Methods: Qualitative interviews were conducted with participants over multiple sessions in which they performed a range of basic functional tasks and simulated industrial tasks using a powered exoskeleton prototype, to understand their expectations of the human-technology partnership, any challenges that arose in their interaction with the device, and what strategies they used to resolve such challenges. Results: Analysis of the data revealed two overarching themes: 1) Participants faced physical, cognitive, and affective challenges to synchronizing with the exoskeleton; and 2) they engaged in sensemaking strategies such as drawing analogies with known prior experiences and anthropomorphized the exoskeleton as a partner entity in order to adapt and address challenges. Discussion: This research is an important first step to understanding how humans make sense of and adapt to a powerful and complex wearable robot with which they must synchronize in order to perform tasks. Implications for our understanding of human and machine agency as well as bidirectional coadaptation principles are discussed.
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PURPOSE: This study aimed to evaluate the use of active surgical co-management (SCM) by medical hospitalists for urology inpatient care. MATERIALS AND METHODS: Since March 2019, a hospitalist-SCM program was implemented at a tertiary-care medical center, and a retrospective cohort study was conducted among co-managed urology inpatients. We assessed the clinical outcomes of urology inpatients who received SCM and compared passive SCM (co-management of patients by hospitalists only on request; March 2019 to June 2020) with active SCM (co-management of patients based on active screening by hospitalists; July 2020 to October 2021). We also evaluated the perceptions of patients who received SCM toward inpatient care quality, safety, and subjective satisfaction with inpatient care at discharge or when transferred to other wards. RESULTS: We assessed 525 patients. Compared with the passive SCM group (n=205), patients in the active SCM group (n=320) required co-management for a significantly shorter duration (p=0.012) and tended to have a shorter length of stay at the urology ward (p=0.062) and less frequent unplanned readmissions within 30 days of discharge (p=0.095) while triggering significantly fewer events of rapid response team activation (p=0.002). No differences were found in the proportion of patients transferred to the intensive care unit, in-hospital mortality rates, or inpatient care questionnaire scores. CONCLUSION: Active surveillance and co-management of urology inpatients by medical hospitalists can improve the quality and efficacy of inpatient care without compromising subjective inpatient satisfaction.
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Hospitalists , Urology , Humans , Inpatients , Retrospective Studies , Tertiary Care CentersABSTRACT
The demand for deep learning frameworks capable of running in edge computing environments is rapidly increasing due to the exponential growth of data volume and the need for real-time processing. However, edge computing environments often have limited resources, necessitating the distribution of deep learning models. Distributing deep learning models can be challenging as it requires specifying the resource type for each process and ensuring that the models are lightweight without performance degradation. To address this issue, we propose the Microservice Deep-learning Edge Detection (MDED) framework, designed for easy deployment and distributed processing in edge computing environments. The MDED framework leverages Docker-based containers and Kubernetes orchestration to obtain a pedestrian-detection deep learning model with a speed of up to 19 FPS, satisfying the semi-real-time condition. The framework employs an ensemble of high-level feature-specific networks (HFN) and low-level feature-specific networks (LFN) trained on the MOT17Det dataset, achieving an accuracy improvement of up to AP50 and AP0.18 on MOT20Det data.
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Indoor fall monitoring is challenging for community-dwelling older adults due to the need for high accuracy and privacy concerns. Doppler radar is promising, given its low cost and contactless sensing mechanism. However, the line-of-sight restriction limits the application of radar sensing in practice, as the Doppler signature will vary when the sensing angle changes, and signal strength will be substantially degraded with large aspect angles. Additionally, the similarity of the Doppler signatures among different fall types makes it extremely challenging for classification. To address these problems, in this paper we first present a comprehensive experimental study to obtain Doppler radar signals under large and arbitrary aspect angles for diverse types of simulated falls and daily living activities. We then develop a novel, explainable, multi-stream, feature-resonated neural network (eMSFRNet) that achieves fall detection and a pioneering study of classifying seven fall types. eMSFRNet is robust to both radar sensing angles and subjects. It is also the first method that can resonate and enhance feature information from noisy/weak Doppler signatures. The multiple feature extractors - including partial pre-trained layers from ResNet, DenseNet, and VGGNet - extracts diverse feature information with various spatial abstractions from a pair of Doppler signals. The feature-resonated-fusion design translates the multi-stream features to a single salient feature that is critical to fall detection and classification. eMSFRNet achieved 99.3% accuracy detecting falls and 76.8% accuracy for classifying seven fall types. Our work is the first effective multistatic robust sensing system that overcomes the challenges associated with Doppler signatures under large and arbitrary aspect angles, via our comprehensible feature-resonated deep neural network. Our work also demonstrates the potential to accommodate different radar monitoring tasks that demand precise and robust sensing.
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Occupational exoskeletons have become more prevalent as an ergonomic control to reduce the physical demands of workers. While beneficial effects have been reported, there is relatively little evidence regarding potential adverse effects of exoskeletons on fall risk. The purpose of this study was to investigate the effects of a leg-support exoskeleton on reactive balance after simulated slips and trips. Six participants (three females) used a passive, leg-support exoskeleton that provided chair-like support in three experimental conditions (no exoskeleton, low-seat setting, high-seat setting). In each of these conditions, participants were exposed to 28 treadmill perturbations from an upright standing posture simulating a backward slip (0.4-1.6 m/s) or a forward trip (0.75-2.25 m/s). The exoskeleton increased the probability of a failed recovery, and adversely affected reactive balance kinematics, after simulated slips and trips. After simulated slips, the exoskeleton decreased initial step length 0.039 m, decreased mean step speed 0.12 m/s, anteriorly displaced touchdown position of the initial recovery step by 0.045 m, and decreased PSIS height at initial step touchdown by 1.7 % sof its standing height. After simulated trips, the exoskeleton increased trunk angle at step 2.4 degrees, and decreased initial step length 0.033 m. These effects appeared to result from the exoskeleton inhibiting regular stepping motion due to its posterior placement on the lower limbs, added mass, and mechanical constraints on participant movement. Our results suggest care may be needed among leg-support exoskeleton users when at risk of slips or trips and motivate potential exoskeleton design modifications to reduce fall risk.
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Leg , Postural Balance , Female , Humans , Gait , Walking , Biomechanical PhenomenaABSTRACT
Evidence is emerging on how whole-body powered exoskeleton (EXO) use impacts users in basic occupational work scenarios, yet our understanding of how users learn to use this complex technology is limited. We explored how novice users adapted to using an EXO during gait. Six novices and five experienced users completed the study. Novices completed an initial training/familiarization gait session, followed by three subsequent gait sessions using the EXO, while experienced users completed one gait session with the EXO. Spatiotemporal gait measures, pelvis and lower limb joint kinematics, muscle activities, EXO torques, and human-EXO interaction forces were measured. Adaptations among novices were most pronounced in spatiotemporal gait measures, followed by joint kinematics, with smaller changes evident in muscle activity and EXO joint torques. Compared to the experienced users, novices exhibited a shorter step length and walked with significantly greater anterior pelvic tilt and less hip extension. Novices also used lower joint torques from the EXO at the hip and knee, and they had greater biceps femoris activity. Overall, our results may suggest that novices exhibited clear progress in learning, but they had not yet adopted motor strategies similar to those of experienced users after the three sessions. We suggest potential future directions to enhance motor adaptations to powered EXO in terms of both training protocols and human-EXO interfaces.
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Exoskeleton Device , Humans , Pilot Projects , Muscle, Skeletal/physiology , Walking/physiology , Gait/physiology , Biomechanical PhenomenaABSTRACT
Arm-support exoskeletons (ASEs) are an emerging technology with the potential to reduce physical demands during diverse tasks, especially overhead work. However, limited information is available about the effects of different ASE designs during overhead work with diverse task demands. Eighteen participants (gender-balanced) performed lab-based simulations of a pseudo-static overhead task. This task was performed in six different conditions (3 work heights × 2 hand force directions), with each of three ASEs and in a control condition (i.e., no ASE). Using ASEs generally reduced the median activity of several shoulder muscles (by â¼12-60%), changed working postures, and decreased perceived exertion in several body regions. Such effects, though, were often task-dependent and differed between the ASEs. Our results support earlier evidence of the beneficial effects of ASEs for overhead work but emphasize that: 1) these effects depend on the task demands and ASE design and 2) none of the ASE designs tested was clearly superior across the tasks simulated.
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Exoskeleton Device , Humans , Electromyography , Physical Exertion , Arm , Task Performance and Analysis , Posture/physiology , Muscle, Skeletal/physiology , Shoulder/physiology , Biomechanical PhenomenaABSTRACT
Industrial exoskeletons are a promising ergonomic intervention to reduce the risk of work-related musculoskeletal disorders by providing external physical support to workers. Passive exoskeletons, having no power supplies, are of particular interest given their predominance in the commercial market. Understanding the mechanical behavior of the torque generation mechanisms embedded in passive exoskeletons is, however, essential to determine the efficacy of these devices in reducing physical loads (e.g., in manual material handling tasks). We introduce a novel approach using a computerized dynamometer to quantify the assistive torque profiles of two passive back-support exoskeletons (BSEs) at different support settings and in both static and dynamic conditions. The feasibility of this approach was examined using both human subjects and a mannequin. Clear differences in assistive torque magnitudes were evident between the two BSEs, and both devices generated more assistive torques during trunk/hip flexion than extension. Assistive torques obtained from human subjects were often within similar ranges as those from the mannequin, though values were more comparable over a narrow range of flexion/extension angles due to practical limitations with the dynamometer and human subjects. Characterizing exoskeleton assistive torque profiles can help in better understanding how to select a torque profile for given task requirements and user anthropometry, and aid in predicting the potential impacts of exoskeleton use by incorporating measured torque profiles in a musculoskeletal modeling system. Future work is recommended to assess this approach for other occupational exoskeletons.
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Back-support exoskeletons (BSEs) are a promising ergonomic intervention for reducing physical demands on the low-back, but little is known regarding whether BSE use alters balance recovery following external perturbations. Hence, we investigated the effects of wearing a BSE on single-step balance recovery following a forward loss of balance. Sixteen (8 M, 8F) young, healthy participants were released from static forward-leaning postures and attempted to recover their balance with a single step while wearing a BSE (backXTM) with three different levels of support torque (i.e., no torque, low, and high) and in a control condition (no exoskeleton). Lean angle was increased until they failed in two consecutive trials to recover their balance with a single step. The maximum lean angle from which individuals could successfully recover was not significantly altered when wearing the BSE. However, wearing the BSE under all torque conditions increased reaction times. The BSE also impeded hip flexion (i.e., decrease in both peak hip flexion angle and angular velocity), resulting in decreased peak knee flexion velocity, knee range of motion, and step length. Measures of the margin of stability decreased significantly in the high-torque BSE condition. Overall, our results suggest that use of a BSE that provides external hip extension torque impairs balance recovery responses. Future work extending kinetic analyses to recovery responses, as well as a study of recovery when responding to slips and trips while walking, would offer a more complete picture of how a BSE may impact balance recovery following a loss of balance.
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Aging , Postural Balance , Humans , Postural Balance/physiology , Biomechanical Phenomena , Aging/physiology , Walking/physiologyABSTRACT
BACKGROUND: Hospitalists are becoming increasingly involved in end-of-life (EOL) care decision making. They participate in the completion of physician orders for life-sustaining treatment (POLST) for patients who have not yet decided whether to proceed with life-sustaining treatment (LST) at the EOL. However, hospitalists are not physicians who have continuously treated patients in outpatient settings; hence, the continuity of care may be poor. We aimed to analyze the effect of outpatient physician involvement on the POLST completed by hospitalists. METHODS: A retrospective cohort study was conducted in patients aged 18 years or older treated by hospitalists who completed POLST at Seoul National University Bundang Hospital from February 2018 to March 2020. The clinical and sociodemographic data were obtained through a medical chart review, and the differences in the characteristics of POLST were analyzed depending on the status of outpatient physician involvement. RESULTS: A total of 3,533 POLST forms were written, of which 175 (5.22%) were completed by the hospitalists. The proportion of POLSTs completed by hospitalists gradually increased from 2.53% in 2018 to 4.58% in 2019 and 15.9% in 2020. A total of 144 (82.3%) patients had malignancies, while 31 (17.7%) patients had non-cancer illnesses. In 47.4% of the patients, outpatient physicians were involved in completing physician's orders for LST. When the outpatient physicians were involved, more patients signed the POLST form themselves (P=0.02) and chose comfort measures only when asked to determine their preferred LST type (P=0.00). CONCLUSIONS: The completion of POLST by hospitalists is gradually increasing. LST was reduced when the outpatient physicians participated in the completion of POLST. Using measures to increase the involvement of outpatient providers in goal care discussions, the quality and goal concordance of EOL care can be improved.
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Advance Care Planning , Hospitalists , Terminal Care , Advance Directives , Cross-Sectional Studies , Humans , Outpatients , Resuscitation Orders , Retrospective StudiesABSTRACT
BACKGRUOUND: No consensus exists regarding the early use of subcutaneous (SC) basal insulin facilitating the transition from continuous intravenous insulin infusion (CIII) to multiple SC insulin injections in patients with severe hyperglycemia other than diabetic ketoacidosis. This study evaluated the effect of early co-administration of SC basal insulin with CIII on glucose control in patients with severe hyperglycemia. METHODS: Patients who received CIII for the management of severe hyperglycemia were divided into two groups: the early basal insulin group (n=86) if they received the first SC basal insulin 0.25 U/kg body weight within 24 hours of CIII initiation and ≥4 hours before discontinuation, and the delayed basal insulin group (n=79) if they were not classified as the early basal insulin group. Rebound hyperglycemia was defined as blood glucose level of >250 mg/dL in 24 hours following CIII discontinuation. Propensity score matching (PSM) methods were additionally employed for adjusting the confounding factors (n=108). RESULTS: The rebound hyperglycemia incidence was significantly lower in the early basal insulin group than in the delayed basal insulin group (54.7% vs. 86.1%), despite using PSM methods (51.9%, 85.2%). The length of hospital stay was shorter in the early basal insulin group than in the delayed basal insulin group (8.5 days vs. 9.6 days, P=0.027). The hypoglycemia incidence did not differ between the groups. CONCLUSION: Early co-administration of basal insulin with CIII prevents rebound hyperglycemia and shorten hospital stay without increasing the hypoglycemic events in patients with severe hyperglycemia.