Three Perspectives on Older Adults' Daily Performance, Health, and Technology Use During COVID-19: Focus Group Study.

Background: During COVID-19 lockdowns, older adults' engagement in daily activities was severely affected, causing negative physical and mental health implications. Technology flourished as a means of performing daily activities in this complex situation; however, older adults often struggled to effectively use these opportunities. Despite the important role of older adults' social environments-including their families and health professionals-in influencing their technology use, research into their unique perspectives is lacking. Objective: This study aimed to explore the daily activity performance, health, and technology use experiences of healthy independent Israeli adults (aged ≥65 years) during COVID-19 from a 3-dimensional perspective: older adults, older adults' family members, and health professionals. Methods: Nine online focus groups, averaging 6-7 participants per group, were conducted with older adults, family members, and health professionals (N=59). Data were analyzed using thematic analysis and constant comparative methods. Results: The intertwining of daily activity performance and health emerged as a central theme, with differences between the groups. Older adults prioritized their self-fulfilling routines based on motivation and choice, especially in social-familial activities. In contrast, family members and health professionals focused on serious physical and mental health COVID-19-related consequences. A consensus among all three groups revealed the meaningful role of technology use during this period in bridging functional limitations. Participants delved into technology's transformative power, focusing on the need for technology to get engaged in daily activities. Conclusions: This study illustrates the profound interplay between daily activity performances, physical and mental health, and technology use, using a 3-dimensional approach. Its focus on technology's uses and benefits sheds light on what older adults need to increase their technology use. Interventions for improving digital activity performance can be tailored to meet older adults' needs and preferences by focusing on motivational and preference-related activities.

The International Functional Electrical Stimulation Society (IFESS): Highlights from the IFESS conference at Rehabweek 2023.

The annual conference of the International Functional Electrical Stimulation Society (IFESS) was held in conjunction with the 7th RehabWeek Congress, from September 24 to 28, 2023 at the Resorts World Convention Centre on Sentosa Island, in Singapore. The Congress was a joint meeting of the International Consortium on Rehabilitation Technology (ICRT) together with 10 other societies in the field of assistive technology and rehabilitation engineering. The conference features comprehensive blend of technical and clinical context of FES, a sustained value the society has offered over many years. The cross- and inter- disciplinary approach of medicine, engineering, and science practiced in the FES community had enabled vibrant interaction, creation, and development of impactful and novel contributions to the field of FES, translating FES directly into highly relevant and sustainable solutions for the users.

Automatic Spontaneous Speech Analysis for the Detection of Cognitive Functional Decline in Older Adults: Multilanguage Cross-Sectional Study.

BACKGROUND: The rise in life expectancy is associated with an increase in long-term and gradual cognitive decline. Treatment effectiveness is enhanced at the early stage of the disease. Therefore, there is a need to find low-cost and ecological solutions for mass screening of community-dwelling older adults. OBJECTIVE: This work aims to exploit automatic analysis of free speech to identify signs of cognitive function decline. METHODS: A sample of 266 participants older than 65 years were recruited in Italy and Spain and were divided into 3 groups according to their Mini-Mental Status Examination (MMSE) scores. People were asked to tell a story and describe a picture, and voice recordings were used to extract high-level features on different time scales automatically. Based on these features, machine learning algorithms were trained to solve binary and multiclass classification problems by using both mono- and cross-lingual approaches. The algorithms were enriched using Shapley Additive Explanations for model explainability. RESULTS: In the Italian data set, healthy participants (MMSE score≥27) were automatically discriminated from participants with mildly impaired cognitive function (20≤MMSE score≤26) and from those with moderate to severe impairment of cognitive function (11≤MMSE score≤19) with accuracy of 80% and 86%, respectively. Slightly lower performance was achieved in the Spanish and multilanguage data sets. CONCLUSIONS: This work proposes a transparent and unobtrusive assessment method, which might be included in a mobile app for large-scale monitoring of cognitive functionality in older adults. Voice is confirmed to be an important biomarker of cognitive decline due to its noninvasive and easily accessible nature.

Medium-term patient's satisfaction after primary total knee arthroplasty: enhancing prediction for improved care.

BACKGROUND: Patient-reported satisfaction after total knee arthroplasty (TKA) is low compared to other orthopedic procedures. Although several factors have been reported to influence TKA outcomes, it is still challenging to identify patients who will experience dissatisfaction five years after surgery, thereby improving their management. Indeed, both perioperative information and follow-up questionnaires seem to lack statistical predictive power. HYPOTHESIS: This study aims to demonstrate that machine learning can improve the prediction of patient satisfaction, especially when classical statistics fail to identify complex patterns that lead to dissatisfaction. PATIENTS AND METHODS: Patients who underwent primary TKA were included in a Registry that collected baseline data and clinical outcomes at different follow-ups. The patients were divided into satisfied and dissatisfied groups based on a satisfaction questionnaire administered five years after surgery. Satisfaction was predicted using linear statistical models compared to machine learning algorithms. RESULTS: A total of 147 subjects were analyzed. Regarding statistics, significant differences between satisfaction levels started emerging only six months after the intervention, and the classification was close to random guessing. However, machine learning algorithms could improve the prediction by 72% soon after the intervention, and an improvement of 178% was possible when including follow-ups up to one year. DISCUSSION: This study demonstrates the feasibility of a registry-based approach for monitoring and predicting satisfaction using ML algorithms. LEVEL OF EVIDENCE: III.

"You Need to Set a Daily Schedule": Understanding Successful Aging via Three-Sided Viewpoints.

This study aimed to identify the constructs related to successful aging in the context of engagement in social and productive activities. A qualitative design was used to explore three viewpoints on the aging period with 9 focus groups (3 each for adults 65 years or older, older adults' family members, and health professionals) and 18 interviews with older adults (older adults Mage = 71.7 years, Standard Deviation = 4.62). The transcripts were analyzed using constructivist grounded theory principles. Three categories were identified for successful aging: (a) engagement with life, including social participation, fixed/flexible schedule, time, and meaningful occupation; (b) self-management abilities, including producing daily schedules, independence, and initiation/striving toward goals; and (c) diversity among older adults, including their views on retirement, being active or not, and their dreams/values/goals. Considering the diverse nature of older adults, recognizing the importance of life engagement and self-management abilities emphasizes the necessity for an occupation-based, self-tailored approach to enable successful aging.

Movement Sonification Techniques to Improve Balance in Parkinson's Disease: A Pilot Randomized Controlled Trial.

BACKGROUND: Movement sonification has been recently introduced into the field of neuromotor rehabilitation alongside Neurologic Music Therapy and music-based interventions. This study introduces the use of musical auditory cues encompassing the melodic-harmonic aspect of music. METHODS: Nineteen patients with Parkinson's disease were randomly assigned to the experimental (n = 10) and control (n = 9) groups and underwent thrice-weekly sessions of the same gait training program, with or without sonification. Functional and motor parameters, as well as fatigue, quality of life, and the impact of intervention on patients' well-being, were assessed at baseline (PRE), the end of treatment (POST), and at follow-up (FU). Between-group differences were assessed for each outcome measure using linear mixed-effects models. The outcome measure was entered as the dependent variable, group and time as fixed effects, and time by group as the interaction effect. RESULTS: Mini BESTest and Dynamic Gait Index scores significantly improved in the experimental group (p = 0.01 and p = 0.03, respectively) from PRE to FU, demonstrating a significant impact of the sonification treatment on balance. No other significant differences were observed in the outcome measures. CONCLUSIONS: Larger sample sizes are needed to confirm the effectiveness of sonification approaches in Parkinson's disease, as well as in other neurological disorders.

Autism in Preschool-Aged Children: The Effects of COVID-19 Lockdown.

The COVID-19 lockdown affected children, especially those with autism spectrum disorder, due to the disruption in rehabilitation and educational activities. We conducted a cross-sectional study of 315 preschool-aged children, 35 of which had autism, to investigate this impact. A questionnaire was administered to explore socio-demographic status, familiar/home environment, and COVID-19 exposure. The clinical features of autistic subjects were also examined. Seven variables were considered to describe the effect of pandemic: Remote learning, Behavior changes, Home activities, Sleep habits, Night awakenings, Physical activity, Information about the virus. The lockdown had a significant impact on Remote learning, Behavior changes, and Information about the virus in participants with autism. Moreover, we found a worsening in repetitive movements, echolalia, restricted interests, and aggressive behaviors.

Deep Learning and Procrustes Analysis for Early Dysgraphia Risk Detection with a Tablet Application.

Dysgraphia is a neurodevelopmental disorder specific to handwriting. Classical diagnosis is based on the evaluation of speed and quality of the final handwritten text: it is therefore delayed as it is conducted only when handwriting is mastered, in addition to being highly language-dependent and not always easily accessible. This work presents a solution able to anticipate dysgraphia screening when handwriting has not been learned yet, in order to prevent negative consequences on the individuals' academic and daily life. To quantitatively measure handwriting-related characteristics and monitor their evolution over time, we leveraged the Play-Draw-Write iPad application to collect data produced by children from the last year of kindergarten through the second year of elementary school. We developed a meta-model based on deep learning techniques (ensemble techniques and Quasi-SVM) which receives as input raw signals collected after a processing phase based on dimensionality reduction techniques (autoencoder and Time2Vec) and mathematical tools for high-level feature extraction (Procrustes Analysis). The final dysgraphia classifier can identify "at-risk" children with 84.62% Accuracy and 100% Precision more than two years earlier than current diagnostic techniques.

Non-Functional Jaw Muscular Activity in Patients with Disorders of Consciousness Revealed by A Long-Lasting Polygraphy.

The presence of involuntary, non-functional jaw muscle activity (NFJMA) has not yet been assessed in patients with disorders of consciousness (DOC), although the presence of bruxism and other forms of movement disorders involving facial muscles is probably more frequent than believed. In this work, we evaluated twenty-two prolonged or chronic DOC patients with a long-lasting polygraphic recording to verify NFJMA occurrence and assess its neurophysiological patterns in this group of patients. A total of 5 out of 22 patients showed the presence of significant NFJMA with electromyographic patterns similar to what can be observed in non-DOC patients with bruxism, thus suggesting a disinhibition of masticatory motor nuclei from the cortical control. On the other hand, in two DOC patients, electromyographic patterns advised for the presence of myorhythmia, thus suggesting a brainstem/diencephalic involvement. Functional, non-invasive tools such as long-lasting polygraphic recordings should be extended to a larger sample of patients, since they are increasingly important in revealing disorders potentially severe and impacting the quality of life of DOC patients.

Spiral drawing analysis with a smart ink pen to identify Parkinson's disease fine motor deficits.

Introduction: Since the uptake of digitizers, quantitative spiral drawing assessment allowed gaining insight into motor impairments related to Parkinson's disease. However, the reduced naturalness of the gesture and the poor user-friendliness of the data acquisition hamper the adoption of such technologies in the clinical practice. To overcome such limitations, we present a novel smart ink pen for spiral drawing assessment, intending to better characterize Parkinson's disease motor symptoms. The device, used on paper as a normal pen, is enriched with motion and force sensors. Methods: Forty-five indicators were computed from spirals acquired from 29 Parkinsonian patients and 29 age-matched controls. We investigated between-group differences and correlations with clinical scores. We applied machine learning classification models to test the indicators ability to discriminate between groups, with a focus on model interpretability. Results: Compared to control, patients' drawings were characterized by reduced fluency and lower but more variable applied force, while tremor occurrence was reflected in kinematic spectral peaks selectively concentrated in the 4-7 Hz band. The indicators revealed aspects of the disease not captured by simple trace inspection, nor by the clinical scales, which, indeed, correlate moderately. The classification achieved 94.38% accuracy, with indicators related to fluency and power distribution emerging as the most important. Conclusion: Indicators were able to significantly identify Parkinson's disease motor symptoms. Our findings support the introduction of the smart ink pen as a time-efficient tool to juxtapose the clinical assessment with quantitative information, without changing the way the classical examination is performed.

Investigating Visual Perception Impairments through Serious Games and Eye Tracking to Anticipate Handwriting Difficulties.

Dysgraphia is a learning disability that causes handwritten production below expectations. Its diagnosis is delayed until the completion of handwriting development. To allow a preventive training program, abilities not directly related to handwriting should be evaluated, and one of them is visual perception. To investigate the role of visual perception in handwriting skills, we gamified standard clinical visual perception tests to be played while wearing an eye tracker at three difficulty levels. Then, we identified children at risk of dysgraphia through the means of a handwriting speed test. Five machine learning models were constructed to predict if the child was at risk, using the CatBoost algorithm with Nested Cross-Validation, with combinations of game performance, eye-tracking, and drawing data as predictors. A total of 53 children participated in the study. The machine learning models obtained good results, particularly with game performances as predictors (F1 score: 0.77 train, 0.71 test). SHAP explainer was used to identify the most impactful features. The game reached an excellent usability score (89.4 ± 9.6). These results are promising to suggest a new tool for dysgraphia early screening based on visual perception skills.

Video-based Goniometer Applications for Measuring Knee Joint Angles during Walking in Neurological Patients: A Validity, Reliability and Usability Study.

Easy-to-use evaluation of Range Of Motion (ROM) during walking is necessary to make decisions during neurological rehabilitation programs and during follow-up visits in clinical and remote settings. This study discussed goniometer applications (DrGoniometer and Angles - Video Goniometer) that measure knee joint ROM during walking through smartphone cameras. The primary aim of the study is to test the inter-rater and intra-rater reliability of the collected measurements as well as their concurrent validity with an electro-goniometer. The secondary aim is to evaluate the usability of the two mobile applications. A total of 22 patients with Parkinson's disease (18 males, age 72 (8) years), 22 post-stroke patients (17 males, age 61 (13) years), and as many healthy volunteers (8 males, age 45 (5) years) underwent knee joint ROM evaluations during walking. Clinicians and inexperienced examiners used the two mobile applications to calculate the ROM, and then rated their perceived usability through the System Usability Scale (SUS). Intraclass correlation coefficients (ICC) and correlation coefficients (corr) were calculated. Both applications showed good reliability (ICC > 0.69) and validity (corr > 0.61), and acceptable usability (SUS > 68). Smartphone-based video goniometers could be used to assess the knee ROM during walking in neurological patients, because of their acceptable degree of reliability, validity and usability.

Implementing functional electrical stimulation clinical practice guidelines to support mobility: A stakeholder consultation.

Functional Electrical Stimulation (FES) has been used to support mobility for people with upper motor neuron conditions such as stroke and multiple sclerosis for over 25 years. Recent development and publication of clinical practice guidelines (CPGs) provide evidence to guide clinical decision making for application of FES to improve mobility. Understanding key barriers to the implementation of these CPGs is a critical initial step necessary to create tailored knowledge translation strategies. A public involvement and engagement consultation was conducted with international stakeholders including researchers, clinicians and engineers working with FES to inform implementation strategies for CPG use internationally. Reflexive thematic analysis of the consultation transcripts revealed themes including inconsistent use of CPGs, barriers to implementation such as limited access to FES and low clinician confidence, and the need for a tiered education approach with ongoing support. Insights derived from this consultation will inform the development of knowledge translation strategies to support the next steps to implementing FES use for mobility.

Investigating the effects of COVID-19 lockdown on Italian children and adolescents with and without neurodevelopmental disorders: a cross-sectional study.

We conducted a cross-sectional study to compare the impact of social distancing and lifestyle changes that occurred during Corona Virus Disease 2019 (COVID-19) lockdown on children and adolescents with and without Neurodevelopmental Disorders (NDDs). An online questionnaire was administered in order to investigate the effects of NDD condition, socio-demographic status, familiar/home environment and COVID-19 exposure on their lives during a two months period of social isolation. We used logistic regression, focusing on five endpoints (remote learning, lifestyle, stress/anxiety, sociality, scolding) to define the extent of these effects. Most questions were paired up to parents and children, to verify the occurrence of agreement. 8305 questionnaires were analyzed, 1362 of which completed by NDDs and 6943 by controls. Results showed that the presence of a NDD, compared to controls, had a significant impact on: Remote Learning (i.e. subjects with NDDs experienced more difficulties in attending online classes and studying), Sociality (i.e. subjects with NDDs missed their schoolmates less), Scolding (i.e. subjects with NDDs were scolded more often) and Anxiety (i.e. subjects with NDDs were perceived by their parents as more anxious). Substantial agreement between parents and children arose from questions concerning Remote learning, Lifestyle and Scolding. The current study actually points out that having a NDD gives account for a stronger influence on school performance and on behavioral and psychological aspects, during a two months lockdown. Such results may provide useful information to governments and school authorities on how carrying through supportive strategies for youth affected by NDDs. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-021-02321-2.

Integrating Social Assistive Robots, IoT, Virtual Communities and Smart Objects to Assist at-Home Independently Living Elders: the MoveCare Project.

The integration of Ambient Assisted Living (AAL) frameworks with Socially Assistive Robots (SARs) has proven useful for monitoring and assisting older adults in their own home. However, the difficulties associated with long-term deployments in real-world complex environments are still highly under-explored. In this work, we first present the MoveCare system, an unobtrusive platform that, through the integration of a SAR into an AAL framework, aimed to monitor, assist and provide social, cognitive, and physical stimulation in the own houses of elders living alone and at risk of falling into frailty. We then focus on the evaluation and analysis of a long-term pilot campaign of more than 300 weeks of usages. We evaluated the system's acceptability and feasibility through various questionnaires and empirically assessed the impact of the presence of an assistive robot by deploying the system with and without it. Our results provide strong empirical evidence that Socially Assistive Robots integrated with monitoring and stimulation platforms can be successfully used for long-term support to older adults. We describe how the robot's presence significantly incentivised the use of the system, but slightly lowered the system's overall acceptability. Finally, we emphasise that real-world long-term deployment of SARs introduces a significant technical, organisational, and logistical overhead that should not be neglected nor underestimated in the pursuit of long-term robust systems. We hope that the findings and lessons learned from our work can bring value towards future long-term real-world and widespread use of SARs.

Identification and characterization of learning weakness from drawing analysis at the pre-literacy stage.

Handwriting learning delays should be addressed early to prevent their exacerbation and long-lasting consequences on whole children's lives. Ideally, proper training should start even before learning how to write. This work presents a novel method to disclose potential handwriting problems, from a pre-literacy stage, based on drawings instead of words production analysis. Two hundred forty-one kindergartners drew on a tablet, and we computed features known to be distinctive of poor handwriting from symbols drawings. We verified that abnormal features patterns reflected abnormal drawings, and found correspondence in experts' evaluation of the potential risk of developing a learning delay in the graphical sphere. A machine learning model was able to discriminate with 0.75 sensitivity and 0.76 specificity children at risk. Finally, we explained why children were considered at risk by the algorithms to inform teachers on the specific weaknesses that need training. Thanks to this system, early intervention to train specific learning delays will be finally possible.

Analysis of Genetic Variants Associated with COVID-19 Outcome Highlights Different Distributions among Populations.

The clinical spectrum of SARS-CoV-2 infection ranges from asymptomatic status to mild infections, to severe disease and death. In this context, the identification of specific susceptibility factors is crucial to detect people at the higher risk of severe disease and improve the outcome of COVID-19 treatment. Several studies identified genetic variants conferring higher risk of SARS-CoV-2 infection and COVID-19 severity. The present study explored their genetic distribution among different populations (AFR, EAS, EUR and SAS). As a result, the obtained data support the existence of a genetic basis for the observed variability among populations, in terms of SARS-CoV-2 infection and disease outcomes. The comparison of ORs distribution for genetic risk of infection as well as for disease outcome shows that each population presents its own characteristics. These data suggest that each country could benefit from a population-wide risk assessment, aimed to personalize the national vaccine programs and the preventative measures as well as the allocation of resources and the access to proper therapeutic interventions. Moreover, the host genetics should be further investigated in order to realize personalized medicine protocols tailored to improve the management of patients suffering from COVID-19.

Validation of Pressure-Sensing Insoles in Patients with Parkinson's Disease during Overground Walking in Single and Cognitive Dual-Task Conditions.

There is a need for unobtrusive and valid tools to collect gait parameters in patients with Parkinson's disease (PD). The novel promising tools are pressure-sensing insoles connected to a smartphone app; however, few studies investigated their measurement properties during simple or challenging conditions in PD patients. This study aimed to examine the validity and reliability of gait parameters computed by pressure-sensing insoles (FeetMe® insoles, Paris, France). Twenty-five PD patients (21 males, mean age: 69 (7) years) completed two walking assessment sessions. In each session, participants walked on an electronic pressure-sensitive walkway (GaitRite®, CIR System Inc., Franklin, NJ, USA) without other additional instructions (i.e., single-task condition) and while performing a concurrent cognitive task (i.e., dual-task condition). Spatiotemporal gait parameters were measured simultaneously using the pressure-sensing insoles and the electronic walkway. Concurrent validity was assessed by correlation coefficients and Bland-Altman methodology. Test-retest reliability was examined by intraclass correlation coefficients (ICC) and minimal detectable changes (MDC). The validity results showed moderate to excellent correlations and good agreement between the two systems. Concerning test-retest reliability, moderate-to-excellent ICC values and acceptable MDC demonstrated the repeatability of the measured gait parameters. Our findings support the use of these insoles as complementary instruments to conventional tools during single and dual-task conditions.

Technology use characteristics among older adults during the COVID-19 pandemic: A cross-cultural survey.

Personal computers, tablets, and smartphones may support older adults' engagement when people are required to stay home and opportunities to engage in meaningful activities are reduced during the COVID-19 period. This study aims to screen older adults' technology-use characteristics across social, leisure, and education domains during the COVID-19 pandemic from a crosscultural viewpoint. The sample included 576 participants aged 60 and older from France (n = 62), Spain (n = 110), and Israel (n = 404). Participants completed the technology-use survey, which consists of questions about their facilities, technology usability, need for adaptations to support technology use, and changes in technology use since COVID-19. Significant differences were found between countries in facilities, χ2 (2) = 25.16, p < .001, and usability, χ2 (2) = 64.14, p < .001, across the three domains. Furthermore, 34% of technological usability was predicted by country and facilities, F (4, 568) = 72.39, p < .001. Participants noted a willingness to use technology if it was adapted for social (61%-73%), leisure (51%-71%), or educational (67%-76%) activities and that they devoted substantially more time to technology across domains (>58%) due to COVID-19. These findings highlight culture and facilities as factors that play an imperative role in supporting and enhancing the usability of technology among older adults.