The impact of a mixed reality technology-driven health enhancing physical activity program among community-dwelling older adults: a study protocol.

Background: Physical inactivity and a sedentary lifestyle among community-dwelling older adults poses a greater risk for progressive physical and cognitive decline. Mixed reality technology-driven health enhancing physical activities such as the use of virtual coaches provide an emerging and promising solution to support healthy lifestyle, but the impact has not been clearly understood. Methods and analysis: An observational explanatory sequential mixed-method research design was conceptualized to examine the potential impact of a user-preferred mixed reality technology-driven health enhancing physical activity program directed toward purposively selected community-dwelling older adults in two senior centers in the Philippines. Quantitative components of the study will be done through a discreet choice experiment and a quasi-experimental study. A total of 128, or 64 older adults in each center, will be recruited via posters at community senior centers who will undergo additional screening or health records review by a certified gerontologist to ensure safety and proper fit. Treatments (live coaching with video-based exercise and mixed reality technology-driven exercise) will be assigned to each of the two senior center sites for the quasi-experiment. The participants from the experimental group shall be involved in the discreet choice experiment, modeling, and usability evaluations. Finally, a qualitative sample of participants (n = 6) as key informants shall be obtained from the experimental group using purposive selection. Discussion: This study protocol will examine the health impact of a promising mixed reality program in health promotion among older adults. The study utilizes a human-centered mixed method research design in technology development and evaluation in the context of developing nations.Clinical trial registration: ClinicalTrials.gov, identifier NCT06136468.

Curricula for teaching end-users to kinesthetically program collaborative robots.

Non-expert users can now program robots using various end-user robot programming methods, which have widened the use of robots and lowered barriers preventing robot use by laypeople. Kinesthetic teaching is a common form of end-user robot programming, allowing users to forgo writing code by physically guiding the robot to demonstrate behaviors. Although it can be more accessible than writing code, kinesthetic teaching is difficult in practice because of users' unfamiliarity with kinematics or limitations of robots and programming interfaces. Developing good kinesthetic demonstrations requires physical and cognitive skills, such as the ability to plan effective grasps for different task objects and constraints, to overcome programming difficulties. How to help users learn these skills remains a largely unexplored question, with users conventionally learning through self-guided practice. Our study compares how self-guided practice compares with curriculum-based training in building users' programming proficiency. While we found no significant differences between study participants who learned through practice compared to participants who learned through our curriculum, our study reveals insights into factors contributing to end-user robot programmers' confidence and success during programming and how learning interventions may contribute to such factors. Our work paves the way for further research on how to best structure training interventions for end-user robot programmers.

The relationship between older adults' technology use, in-person engagement, and pandemic-related mental health.

OBJECTIVE: The objectives of this study are to 1) describe changes in in-person communication/activity and changes in older adult technology use during the COVID-19 pandemic and 2) examine whether less in-person communication/activity mediates the relationship between pandemic-related mental health and technology use. METHOD: Linear regressions (stratified by age and financial strain) and structural equation modeling were employed using a nationally representative, cross-sectional survey of 3,188 older adults from the 2020 National Health and Aging Trends Study's COVID-19 Questionairre. RESULTS: Older adults engaged in more technology-based activity (b = 0.24; p<.001), more technology-based health care communication (b = 0.22; p<.001), and more technology-based food acquisition (b = 0.21; p<.001) during the COVID-19 pandemic, as compared to before the pandemic. Results indicate that adults <80 years old demonstrated greater increases in technology-based activity, technology-based health communication, and technology-based food acquisition, compared to adults ≥80 years old. Change in in-person communication significantly mediated the relationship between pandemic-related mental health and technology-based communication (standardized coefficient= -0.012; p=.005), and change in in-person activity significantly mediated the relationship between pandemic-related mental health and technology-based activity (standardized coefficient= -0.017; p=.020). CONCLUSIONS: This study suggests that older adults are utilizing technology more, and therefore should be considered in technology design and dissemination. Technology use could be an important positive response to help those with pandemic related worries stay safely engaged with friends and family. Technologies should be produced that are modifiable for older adults with disabilities and affordable for older adults with fixed incomes.

Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review.

Transparency in Machine Learning (ML), often also referred to as interpretability or explainability, attempts to reveal the working mechanisms of complex models. From a human-centered design perspective, transparency is not a property of the ML model but an affordance, i.e., a relationship between algorithm and users. Thus, prototyping and user evaluations are critical to attaining solutions that afford transparency. Following human-centered design principles in highly specialized and high stakes domains, such as medical image analysis, is challenging due to the limited access to end users and the knowledge imbalance between those users and ML designers. To investigate the state of transparent ML in medical image analysis, we conducted a systematic review of the literature from 2012 to 2021 in PubMed, EMBASE, and Compendex databases. We identified 2508 records and 68 articles met the inclusion criteria. Current techniques in transparent ML are dominated by computational feasibility and barely consider end users, e.g. clinical stakeholders. Despite the different roles and knowledge of ML developers and end users, no study reported formative user research to inform the design and development of transparent ML models. Only a few studies validated transparency claims through empirical user evaluations. These shortcomings put contemporary research on transparent ML at risk of being incomprehensible to users, and thus, clinically irrelevant. To alleviate these shortcomings in forthcoming research, we introduce the INTRPRT guideline, a design directive for transparent ML systems in medical image analysis. The INTRPRT guideline suggests human-centered design principles, recommending formative user research as the first step to understand user needs and domain requirements. Following these guidelines increases the likelihood that the algorithms afford transparency and enable stakeholders to capitalize on the benefits of transparent ML.

Evaluation of Socially-Aware Robot Navigation.

As mobile robots are increasingly introduced into our daily lives, it grows ever more imperative that these robots navigate with and among people in a safe and socially acceptable manner, particularly in shared spaces. While research on enabling socially-aware robot navigation has expanded over the years, there are no agreed-upon evaluation protocols or benchmarks to allow for the systematic development and evaluation of socially-aware navigation. As an effort to aid more productive development and progress comparisons, in this paper we review the evaluation methods, scenarios, datasets, and metrics commonly used in previous socially-aware navigation research, discuss the limitations of existing evaluation protocols, and highlight research opportunities for advancing socially-aware robot navigation.

Multifunctional nanoparticles for targeting the tumor microenvironment to improve synergistic drug combinations and cancer treatment effects.

Docetaxel-based chemotherapy for prostate cancer is the clinical standard of care. However, nonspecific targeting, multiple drug resistance, and adverse side effects are common obstacles. Various natural compounds, including epigallocatechin-3-gallate (EGCG) in combination with taxane, have the potential to be developed as anticancer therapeutics. Although synergistic hydrophobic-hydrophilic combination drugs have been used with some success, the main drawbacks of this approach are poor bioavailability, unfavorable pharmacokinetics, and low tissue distribution. To improve their synergistic effect and overcome limitations, we encapsulated EGCG and low-dose docetaxel within TPGS-conjugated hyaluronic acid and fucoidan-based nanoparticles. This approach might facilitate simultaneous target-specific markers at the edge and center of the tumor and then might increase intratumoral drug accumulation. Additionally, the successful release of bioactive combination drugs was regulated by the pH-sensitive nanoparticles and internalization into prostate cancer cells through CD44 and P-selectin ligand recognition, and the inhibition of cell growth via induced G2/M phase cell cycle arrest was observed in in vitro study. In in vivo studies, treatment with cancer-targeted combination drug-loaded nanoparticles significantly attenuated tumor growth and increased M30 protein expression without causing organ damage. Overall, the multifunctional nanoparticle system improved the drugs' synergistic effect, indicating great potential in its development as a prostate cancer treatment.

The duration of endocrine therapy and breast cancer patients' survival: A nationwide population-based cohort study.

As research progressed, the recommended duration of endocrine therapy for breast cancer patients has been extended from 5 to 10 years. This study aimed to investigate how the duration of endocrine medication and therapy affect survival rate in the real world. By using the National Health Insurance Research Database (NHIRD), this study examined 1002 breast cancer patients newly diagnosed between 2000 and 2005 as research subjects, and conducted follow-up until 2013. Among these subjects, 51 used aromatase inhibitors (AIs), 561 used tamoxifen, and 390 alternated between the use of tamoxifen and AIs. The mean follow-up period in this study was 9.63 years, and the mean duration of taking endocrine medication was 4.04 years. The tamoxifen group had the longest follow-up period (9.87 years), shortest endocrine therapy duration (3.29 years), and best survival rate (86.1%). Patients were divided into 3 groups based on the duration of endocrine therapy: under 2 years, 2 to 5 years, and over 5 years. It was found that patients who received medication for less than 2 years showed the lowest survival rate with statistically significant differences (P < .001). Therefore, the extension of endocrine therapy duration is critical in improving breast cancer patients' survival rate.

Improving social skills in children with ASD using a long-term, in-home social robot.

Social robots can offer tremendous possibilities for autism spectrum disorder (ASD) interventions. To date, most studies with this population have used short, isolated encounters in controlled laboratory settings. Our study focused on a 1-month, home-based intervention for increasing social communication skills of 12 children with ASD between 6 and 12 years old using an autonomous social robot. The children engaged in a triadic interaction with a caregiver and the robot for 30 min every day to complete activities on emotional storytelling, perspective-taking, and sequencing. The robot encouraged engagement, adapted the difficulty of the activities to the child's past performance, and modeled positive social skills. The system maintained engagement over the 1-month deployment, and children showed improvement on joint attention skills with adults when not in the presence of the robot. These results were also consistent with caregiver questionnaires. Caregivers reported less prompting over time and overall increased communication.

Using gaze patterns to predict task intent in collaboration.

In everyday interactions, humans naturally exhibit behavioral cues, such as gaze and head movements, that signal their intentions while interpreting the behavioral cues of others to predict their intentions. Such intention prediction enables each partner to adapt their behaviors to the intent of others, serving a critical role in joint action where parties work together to achieve a common goal. Among behavioral cues, eye gaze is particularly important in understanding a person's attention and intention. In this work, we seek to quantify how gaze patterns may indicate a person's intention. Our investigation was contextualized in a dyadic sandwich-making scenario in which a "worker" prepared a sandwich by adding ingredients requested by a "customer." In this context, we investigated the extent to which the customers' gaze cues serve as predictors of which ingredients they intend to request. Predictive features were derived to represent characteristics of the customers' gaze patterns. We developed a support vector machine-based (SVM-based) model that achieved 76% accuracy in predicting the customers' intended requests based solely on gaze features. Moreover, the predictor made correct predictions approximately 1.8 s before the spoken request from the customer. We further analyzed several episodes of interactions from our data to develop a deeper understanding of the scenarios where our predictor succeeded and failed in making correct predictions. These analyses revealed additional gaze patterns that may be leveraged to improve intention prediction. This work highlights gaze cues as a significant resource for understanding human intentions and informs the design of real-time recognizers of user intention for intelligent systems, such as assistive robots and ubiquitous devices, that may enable more complex capabilities and improved user experience.

Endocavity Ultrasound Probe Manipulators.

We developed two similar structure manipulators for medical endocavity ultrasound probes with 3 and 4 degrees of freedom (DoF). These robots allow scanning with ultrasound for 3-D imaging and enable robot-assisted image-guided procedures. Both robots use remote center of motion kinematics, characteristic of medical robots. The 4-DoF robot provides unrestricted manipulation of the endocavity probe. With the 3-DoF robot the insertion motion of the probe must be adjusted manually, but the device is simpler and may also be used to manipulate external-body probes. The robots enabled a novel surgical approach of using intraoperative image-based navigation during robot-assisted laparoscopic prostatectomy (RALP), performed with concurrent use of two robotic systems (Tandem, T-RALP). Thus far, a clinical trial for evaluation of safety and feasibility has been performed successfully on 46 patients. This paper describes the architecture and design of the robots, the two prototypes, control features related to safety, preclinical experiments, and the T-RALP procedure.

Effects of moderate alcohol consumption on inflammatory biomarkers.

OBJECTIVES: Although light to moderate alcohol consumption has been associated with lower all-cause and cardiovascular (CV) mortality, the underlying mechanisms are only partly understood. Evidence has emerged in recent years that atherosclerosis is an inflammatory disease. We hypothesize that beneficial effects of moderate alcohol consumption on CV mortality may be linked to antiinflammatory effects. METHODS AND RESULTS: The association between alcohol consumption and concentrations of high sensitivity C-reactive protein (hs-CRP) and fibrinogen were investigated. Six hundred and thirtysix eligible individuals apparently healthy were included. 393 (61.8%) were men and 243 (38.2%) were women. The mean ages for men and women were 51.5 +/- 12.4 y and 50.8 +/- 12.1 y, respectively. Daily alcohol intake showed an apparent U-shaped association with hs-CRP and fibrinogen values in men, with lowest levels at an alcohol intake of 20-70 g daily (0.139 +/- 0.116 mg/dl for hs-CRP and 274 +/- 51.7 mg/dl for fibrinogen). Proportional odds model analysis showed moderate alcohol consumption (20 to 70 g vs. no drinking per day, OR = 0.32, 95% CI: 0.14-0.74), and regular exercise (> or = 3 times/week vs. no, OR = 0.52, 95% CI: 0.35-0.77) were negatively correlated with elevated hs-CRP values. CONCLUSIONS: Our results parallel the demonstration of a U-shaped relationship between alcohol consumption and cardiovascular mortality, and suggest that anti-inflammatory effects of moderate alcohol intake may partly be linked to a low cardiovascular and overall mortality.

Live/real time three-dimensional transthoracic echocardiographic assessment of left ventricular volumes, ejection fraction, and mass compared with magnetic resonance imaging.

Due to reliance upon geometric assumptions and foreshortening issues, the traditionally utilized transthoracic two-dimensional echocardiography (2DTTE) has shown limitations in assessing left ventricular (LV) volume, mass, and function. Cardiac magnetic resonance imaging (MRI) has shown potential in accurately defining these LV characteristics. Recently, the emergence of live/real time three-dimensional (3D) TTE has demonstrated incremental value over 2DTTE and comparable value with MRI in assessing LV parameters. Here we report 58 consecutive patients with diverse cardiac disorders and clinical characteristics, referred for clinical MRI studies, who were evaluated by cardiac MRI and 3DTTE. Our results show good correlation between the two modalities.

Long-term survival and prognostic implications after coronary artery bypass grafting in Chinese patients with coronary artery disease.

OBJECTIVES: This hospital-based study was conducted to determine the survival rates of patients after coronary artery bypass grafting (CABG) surgery and the associated prognostic factors related to all-cause mortality during a 7-year follow-up in Taiwan. METHODS AND RESULTS: Between January 1997 and December 2003, the medical records of 1877 patients who underwent primary, isolated CABG surgery were studied. The Kaplan-Meier method was used to estimate survival. Multiple Cox regression was used to investigate the independence of prognostic factors associated with all-cause mortality. Of the 1877 patients who underwent CABG surgery, 192 expired during the 7-year study period. The overall patient survival rate was 85.96% (95% CI: 83.74-88.16). Using multiple Cox regression analysis, in addition to female gender, older age at surgery, pulmonary oedema, longer ischaemic time, longer cardiopulmonary bypass time, and poorer postoperative left ventricular ejection fraction were significant factors associated with all-cause mortality for both men and women. Associated prognostic factors varied by gender. For men, smoking (RR = 2.82, 95% CI: 1.06-4.16), respiratory failure (RR = 6.88, 95% CI: 3.29-14.40) and cardiogenic shock (RR = 4.04, 95% CI: 2.13-7.67) were significantly related to all-cause mortality, but not for women. Sepsis (RR = 8.97,95% CI: 1.19-19.81) and ICU stay (RR = 1.03,95% CI: 1.01-1.05) were significantly related to all-cause mortality among female patients only. CONCLUSIONS: Several gender-related differences were noted pertaining to all-cause mortality and the relationships between smoking, sepsis, respiratory failure, cardiogenic shock, and ICU stay.

Hyaluronate improves pain, physical function and balance in the geriatric osteoarthritic knee: a 6-month follow-up study using clinical tests.

OBJECTIVE: To investigate the effects of intraarticular hyaluronic acid (HA) (Artzal, Seikagaku Corp., Japan) in geriatric participants with unilateral knee osteoarthritis (OA). METHOD: This was a prospective, observer-blind study with 6 months follow-up done in the setting of an outpatient rehabilitation department in a university-affiliated tertiary care medical center. Sixty-eight patients, aged 65 years or above, with symptoms and radiographic evidence of unilateral knee OA for at least 6 months were recruited. Patients received five weekly intraarticular injections of Artzal into symptomatic knees. Fifty-six participants completed the study. Fifty age-, body mass- and gender-matched healthy individuals were selected as control. Visual analog scale (VAS), Lequesne index and four balance tests including single-leg stance test (SLS), function reach test (FRT), timed "Up-and-Go" test (TUG) and Berg balance scale (BBS) were assessed before injection and at each follow-up visit in the OA group. Four balance tests were obtained on healthy participants for data comparison. RESULTS: Before Artzal injections, the OA group showed significantly worse VAS, Lequesne index and four balance tests scores than did the control group (P < 0.001). Significant improvement in all outcome measures were noted at 1 week, 1, 3 and 6 months post the fifth injection compared with baseline before injection. Local adverse events were reported in four patients (7.1%). CONCLUSION: Significant improvement in pain, physical function and balance tests was demonstrated after five weekly Artzal injections in geriatric patients with knee OA. The effect had rapid onset at 1 week and may last for 6 months.

Long-term survival of non-elderly patients with severe heart failure treated with angiotensin-converting enzyme inhibitors assessment of treatment with captopril and enalapril survival study (ACESS).

The present study examined the effect of treatment with angiotensin-converting enzyme inhibitors (ACEIs) on the long-term prognosis in 119 patients with dilated cardiomyopathy (DCM). Conventional therapy was used in 29 patients and 90 patients were treated with ACEIs: 50 were taking captopril and 40 were taking enalapril; 24 were taking > or = 75 mg captopril or > or = 20 mg enalapril daily (high-dose group) and 66 patients received smaller doses (low-dose group). No significant differences between groups were detected with respect to demographics and clinical signs of congestive heart failure (CHF). During follow-up, 65 patients survived and 54 patients died: 34 patients were in group 1 and 20 patients were in the placebo group. Patients treated with ACEIs had a significantly better survival during the first to third year, but the difference was not significant between the high- and low-dose groups. Comparison of the cumulative probability of death in the enalapril and captopril groups showed a trend of significant reduction of mortality by 13% in the enalapril group (p<0.10). These data indicate that ACEIs have a beneficial effect on prolonging the short- and long-term survival in DCM patients, so it is strongly recommended that all patients with DCM should be treated with ACEIs unless contraindicated. In this study, lower doses of ACEI seemed prognostically equivalent to higher doses, and enalapril appeared to be preferable to captopril in the treatment of severe CHF. Additional prospective large studies are necessary to verify the relationship observed here between the optimal dosage as well as the duration of action of different ACEIs and their outcomes.