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Background: There is increasing evidence to support the efficacy of transcranial direct current stimulation (tDCS) applications in cognitive augmentation and rehabilitation. Neuromodulation achieved with tDCS may further regulate regional cerebral perfusion affiliated through the neurovascular unit; however, components of cerebral perfusion decrease across aging. A novel neuroimaging approach, functional near-infrared spectroscopy (fNIRS), can aid in quantifying these regional perfusional changes. To date, the interaction of the effects of tDCS on cognitive performance across the lifespan and obtained fNIRS hemodynamic responses remain unknown. Objective: This review aims to examine the effects of tDCS on cognitive performance and fNIRS hemodynamic responses within the context of cognitive aging. Methods: Six databases were searched for studies. Quality appraisal and data extraction were conducted by two independent reviewers. Meta-analysis was carried out to determine overall and subgroup effect sizes. Results: Eight studies met inclusion criteria. The overall effect size demonstrates that tDCS can alter cognitive performance and fNIRS signals, with aging being a potential intermediary in tDCS efficacy. Conclusion: From the studies included, the effects of tDCS on cognitive performance and fNIRS metrics are most prominent in young healthy adults and appear to become less robust with increasing age. Given the small number of studies included in this review further investigation is recommended.

Frailty assessment and monitoring are essential for supporting independent living and preventing adverse outcomes among older adults. This study aimed to develop and evaluate the concurrent validity of a high-accuracy home-monitoring system for assessing and tracking frailty in older adults. The system integrated off-the-shelf, zero-effort technologies, including ultra-wideband (UWB) indoor positioning, a smart scale, a connected hand dynamometer, and a Bluetooth speakerphone, to measure the five components of Fried’s Frailty Phenotype criteria. Twenty-one participants (aged 21–90 years) completed frailty assessments using both traditional clinical measures and the sensor-based system within a simulated home environment within a major rehabilitation hospital. The developed system demonstrated very strong and statistically significant correlations between the sensor-based system and the Fried’s Frailty Phenotype criteria, strong correlations with the Clinical Frailty Scale, and moderate-to-strong correlations with the Edmonton Frailty Scale, confirming the system’s strong concurrent validity. These findings indicate that high-accuracy, home-based monitoring technologies can provide reliable, objective, and non-invasive assessment of frailty in older adults, supporting early detection and continuous monitoring. This approach shows promise for future integration into smart home environments to enhance proactive frailty management and aging-in-place strategies.

The prevalence of dementia is expected to rise with an aging population, necessitating accessible early detection methods. Serious games have emerged as potential cognitive screening tools. They provide not only an engaging platform for assessing cognitive function but also serve as valuable indicators of cognitive health through engagement levels observed during play. This study aims to examine the differences in engagement-related behaviors between older adults with and without dementia during serious gaming sessions. Further, it seeks to identify the key contributors that enhance the effectiveness of machine learning for dementia classification based on engagement-related behaviors. This was an exploratory proof-of-concept study. Over 8 weeks, 20 older adults, 6 of whom were living with dementia, were enrolled in a single-case design study. Participants played 1 of 4 \"Vibrant Minds\" serious games (Bejeweled, Whack-A-Mole, Mah-jong, and Word-Search) over 8 weeks (16 30-min sessions). Throughout the study, sessions were recorded to analyze engagement-related behaviors. This paper reports on the analysis of the engagement-related behaviors of 15 participants. The videos of these 15 participants (10 cognitively intact, 5 with dementia) were analyzed by 2 independent raters, individually annotating engagement-related behaviors at 15-second intervals using a coding system. This analysis resulted in 1774 data points categorized into 47 behavior codes, augmented by 54 additional features including personal characteristics, technical issues, and environmental factors. Each engagement-related behavior was compared between older adults living with dementia and older adults without dementia using the χ² test with a 2×2 contingency table with a significance level of .05. Codes underwent one-hot encoding and were processed using random forest classifiers to distinguish between participant groups. Significant differences in 64% of engagement-related behaviors were found between groups, notably in torso movements, voice modulation, facial expressions, and concentration. Including engagement-related behaviors, environmental disturbances, technical issues, and personal characteristics resulted in the best model for classifying cases of dementia correctly, achieving an F1-score of 0.91 (95% CI 0.851-0.963) and an area under the receiver operating curve of 0.99 (95% CI 0.984-1.000). Key features distinguishing between older adults with and without dementia during serious gameplay included torso, voice, facial, and concentration behaviors, as well as age. The best performing machine learning model identified included features of engagement-related behavios, environmental disturbances, technical challenges, and personal attributes. Engagement-related behaviors observed during serious gaming offer crucial markers for identifying dementia. Machine learning models that incorporate these unique behavioral markers present a promising, noninvasive approach for early dementia screening in a variety of settings.

Forearm, wrist, and hand impairments affect many individuals and impose a significant economic burden on health care systems. The FEPSim (flexion, extension, pronation, and supination) is designed for hand and wrist rehabilitation. It could become part of the standard care for upper extremity rehabilitation, aiming to improve range of motion, dexterity, and strength during therapeutic activities. However, the FEPSim has not yet been tested in a health care setting, highlighting the need for a trial to assess its effectiveness in upper extremity rehabilitation. We aim to assess the feasibility of conducting a definitive trial investigating the effectiveness of adding a new device for hand therapy exercises, the FEPSim, to standard care for patients with impairments of the hand, wrist, and forearm. Thirty-eight patients with impairments of distal upper extremities were randomly assigned either to the intervention group (FEPSim and standard care, n=19) or to the control group (standard care, n=19). Therapeutic activities to increase strength, range of motion, resistance, and dexterity were delivered by treating hand therapists using the FEPSim device for the intervention group. Outcome measures included wrist passive and active range of motion, grip strength, pinch grip force, and the Patient-Rated Wrist Evaluation. The trial retention rate (36/38, 95%) and compliance (control group: 100%; intervention group: 89%) were high. The comparisons of the change-from-baseline between groups revealed that in 63.2% (12/19) of the outcome variables, the change was in favor of the FEPSim, with statistically significant improvements in passive wrist flexion (t34=-0.335, P=.008) and grip strength (t34=-1.841, P=.04). The FEPSim was accepted as part of standard care by therapists and patients at 2 hospitals. The trial design was feasible for hand intervention using the FEPSim device. The FEPSim positively affected grip strength, an objective measure of hand functioning.

Background: Upper extremity function plays a critical role in completing activities of daily living, employment, and participating in recreational activities. The FEPSim device is a medical device for hand and wrist rehabilitation that can be adjusted according to the patient’s requirements in rehabilitation. Furthermore, the FEPSim can be used to assess the patient’s strength and range of motion of the forearm, wrist, and hand. At present, the acceptance and usability of the FEPSim have not been tested in a clinical setting, with limited perspectives from rehabilitation-providing clinicians. Objective: This study aims to understand the factors related to the acceptance and usability of the FEPSim device. Upper limb disorders are prevalent across populations. The impact of upper limb disorders, both acute and chronic, puts a significant burden on the Canadian health care system. Methods: A qualitative descriptive study was conducted that involved face-to-face semistructured interviews with hand therapists from hand therapy services who used the FEPSim device. We used purposive sampling to recruit 10 participants over a period of 14 months. Semistructured interview questions (topic-guided) examined the technology acceptance and usability of the FEPSim device. Results: We found 6 factors to be critical aspects of the acceptance and usability of the FEPSim device. These factors were (1) useful for therapy, (2) effortlessness, (3) environmental conditions, (4) internal encouragement, (5) technological aesthetics, and (6) use. Conclusions: The FEPSim device was widely accepted by the therapists. The use of the FEPSim device is a feasible alternative for supporting hand therapy. Trial Registration: ISRCTN Registry ISRCTN13656014; https://www.isrctn.com/ISRCTN13656014

Primary progressive aphasia (PPA) and primary progressive apraxia of speech (PPAOS) are neurodegenerative syndromes characterized by progressive decline in language or speech. There is a growing number of studies investigating speech-language interventions for PPA/PPAOS. An updated systematic evaluation of the treatment evidence is warranted to inform best clinical practice and guide future treatment research. We systematically reviewed the evidence for behavioral treatment for speech and language in this population. Reviewed articles were published in peer-reviewed journals through 31 May 2021. We evaluated level of evidence, reporting quality, and risk of bias using a modified version of the American Speech-Language Hearing Association (ASHA) Levels of Evidence, an appraisal point system, additional reporting quality and internal/external validity items, and, as appropriate, the Single Case Experimental Design Scale or the Physiotherapy Evidence Database – PsycBITE Rating Scale for Randomized and Non-Randomized Controlled Trials . Results were synthesized using quantitative summaries and narrative review. A total of 103 studies reported treatment outcomes for 626 individuals with PPA; no studies used the diagnostic label PPAOS. Most studies evaluated interventions for word retrieval. The highest-quality evidence was provided by 45 experimental and quasi-experimental studies (16 controlled group studies, 29 single-subject designs). All ( k  = 45/45) reported improvement on a primary outcome measure; most reported generalization ( k  = 34/43), maintenance ( k  = 34/39), or social validity ( k  = 17/19) of treatment for at least one participant. The available evidence supports speech-language intervention for persons with PPA; however, treatment for PPAOS awaits systematic investigation. Implications and limitations of the evidence and the review are discussed.

Abstract Background Every 21 seconds an American experiences a Traumatic Brain Injury (TBI), and every 40 seconds, another endures a stroke. These events fall under Acquired Brain Injuries (ABI) with prevalence rates impacted by an aging population. ABI can lead to various physical, cognitive, and mental impairments, emphasizing the need for innovative rehabilitation strategies, including those specific to older adults. Mixed Reality (MR) technologies offer potential in enhancing ABI rehabilitation, yet face challenges such as methodological inconsistencies, differing clinical populations, and exaggerated efficacy claims. Objectives 1) Review MR’s role in ABI rehabilitation among older adults, assessing the implications of aging, clinical, and technological considerations. 2) Present ongoing MR research at the Glenrose Rehabilitation Hospital (GRH, Edmonton, Canada). Methods 1) A systematic review following PRISMA guidelines was performed across seven databases, with two independent reviewers analyzing the data. The analysis emphasized clinical objectives, MR systems, levels of evidence, and technology readiness levels. 2) QR codes that link to videos will highlight the ongoing research and development of MR-delivered ABI rehabilitation at the GRH. Results Twenty-six studies met the inclusion criteria, totalling 453 subjects with ABI (mean age: 60 ± 5.34 years). MR applications mainly targeted upper limb motor rehabilitation, revealing an overall low level of evidence and a median technology readiness level of 6 (prototypes tested in relevant environments). Conclusion Despite existing variability and technological challenges, the promising results stress the importance of ongoing research and innovation in MR rehabilitation. The GRH stands as a key research hub, actively advancing this field.

Abstract Background Frailty, a condition often affecting older adults, increases vulnerability and diminishes physical abilities across bodily systems. Current non-routine frailty screening in primary care or clinical settings fails to detect “hidden health vulnerabilities” in a timely manner. Smart home technologies offer an affordable and effective solution for continuous frailty tracking and prevention. However, existing home monitoring technologies typically require users to acquire new skills or are invasive, such as camera-based systems. Objective: Our goal is to create a high-accuracy home monitoring system coupled with Internet of Things devices to identify potential frailty indicators. Methods This qualitative description study involves 4 to 8 participants, including older adults with and without Mild Cognitive Impairments/frailty, caregivers, and clinicians, in a group interview. Using card sorting and task mapping, the interview seeks to identify and define the features and challenges of a smart home system to monitor frailty in older adults. Results The study is registered in clinical trials, with data collection commencing soon. At the conference, we will present the research protocol and the findings from the analysis of the interviews. Conclusion Through the early engagement of older adults and caregivers, we strive to design a valuable and meaningful system that (1) uses zero-effort technologies so frail older adults do not need to develop new skills in order to use the system; (2) is a non-camera-based tracking technology preserving autonomy and privacy; (3) generates the frailty data meaningful for older adults, caregivers and the health system.

Abstract Older adults admitted to hospital for rehabilitation often have some degree of concomitant cognitive impairment, which may be a barrier to optimizing rehabilitation approaches. Transcranial direct current stimulation (tDCS), a type of non-invasive brain stimulation, delivers a low electrical current across the brain. The neuromodulatory effects of tDCS can be of therapeutic benefit and has been shown to augment cognitive functions in both healthy and clinical populations. This study investigated the effects of tDCS on cognition in older adult inpatients with depression or anxiety. It was hypothesized that anodal tDCS over the left dorsolateral prefrontal cortex would increase cognitive performance compared to a placebo group. Twenty adults between 65 to 86 years of age admitted to the Glenrose Rehabilitation Hospital with underlying depression or anxiety were recruited. Anodal (n=10) or sham (n=10) tDCS stimulation was administered at 1.5mA over 20 minutes, for 10-15 sessions based on participant availability. Cognitive assessments were administered before and after the tDCS protocol. Anodal tDCS stimulation resulted in significant gains on the Symbol Digit Modality Test, Trail Making Test Part A, and Forward Digit Span. This study demonstrated a tDCS-invoked cognitive enhancement in the domains of attention, information processing speed, and short-term memory processes. With the rapidly ageing population, tDCS may be a potential therapeutic option for cognitive enhancement and may be beneficial in ageing-related cognitive-disorders including mild cognitive impairment and dementia.

Growing evidence suggests that human gut microbiome composition and function are highly associated with health and disease. As such, high-throughput metaproteomic studies are becoming more common in gut microbiome research. Metaproteomics is used to explore the functional dynamics of microbial communities. However, acquiring metaproteomic data by tandem mass spectrometry (MS/MS) is time-consuming and resource-intensive, and there is a demand for computational methods that can be used to reduce these resource requirements. We present MetaProClust-MS1, a computational framework for microbiome feature screening developed to prioritize samples for follow-up MS/MS. In this proof-of-concept study, we tested and compared MetaProClust-MS1 results on gut microbiome data, from fecal samples, acquired using short 15-min MS1-only chromatographic gradients and MS1 spectra from longer 60-min gradients to MS/MS-acquired data. We found that MetaProClust-MS1 identified robust gut microbiome responses caused by xenobiotics with significantly correlated cluster topologies of comparable data sets. We also used MetaProClust-MS1 to reanalyze data from both a clinical MS/MS diagnostic study of pediatric patients with inflammatory bowel disease and an experiment evaluating the therapeutic effects of a small molecule on the brain tissue of Alzheimer’s disease mouse models. MetaProClust-MS1 clusters could distinguish between inflammatory bowel disease diagnoses (ulcerative colitis and Crohn’s disease) using samples from mucosal luminal interface samples and identified hippocampal proteome shifts of Alzheimer’s disease mouse models after small-molecule treatment. Therefore, we demonstrate that MetaProClust-MS1 can screen both microbiomes and single-species proteomes using only MS1 profiles, and our results suggest that this approach may be generalizable to any proteomics experiment. MetaProClust-MS1 may be especially useful for large-scale metaproteomic screening for the prioritization of samples for further metaproteomic characterization, using MS/MS, for instance, in addition to being a promising novel approach for clinical diagnostic screening. IMPORTANCE Growing evidence suggests that human gut microbiome composition and function are highly associated with health and disease. As such, high-throughput metaproteomic studies are becoming more common in gut microbiome research. However, using a conventional long liquid chromatography (LC)-MS/MS gradient metaproteomics approach as an initial screen in large-scale microbiome experiments can be slow and expensive. To combat this challenge, we introduce MetaProClust-MS1, a computational framework for microbiome screening using MS1-only profiles. In this proof-of-concept study, we show that MetaProClust-MS1 identifies clusters of gut microbiome treatments using MS1-only profiles similar to those identified using MS/MS. Our approach allows researchers to prioritize samples and treatments of interest for further metaproteomic analyses and may be generally applicable to any proteomic analysis. In particular, this approach may be especially useful for large-scale metaproteomic screening or in clinical settings where rapid diagnostic evidence is required.