Remote at-home wearable-based gait assessments in Progressive Supranuclear Palsy compared to Parkinson's Disease.

BACKGROUND: Wearable sensors can differentiate Progressive Supranuclear Palsy (PSP) from Parkinson's Disease (PD) in laboratory settings but have not been tested in remote settings. OBJECTIVES: To compare gait and balance in PSP and PD remotely using wearable-based assessments. METHODS: Participants with probable PSP or probable/clinically established PD with reliable caregivers, still able to ambulate 10 feet unassisted, were recruited, enrolled, and consented remotely and instructed by video conference to operate a study-specific tablet solution (BioDigit Home ™) and to wear three inertial sensors (LEGSys™, BioSensics LLC, Newton, MA USA) while performing the Timed Up and Go, 5 × sit-to-stand, and 2-min walk tests. PSPRS and MDS-UPDRS scores were collected virtually or during routine clinical visits. RESULTS: Between November, 2021- November, 2022, 27 participants were screened of whom 3 were excluded because of technological difficulties. Eleven PSP and 12 PD participants enrolled, of whom 10 from each group had complete analyzable data. Demographics were well-matched (PSP mean age = 67.6 ± 1.3 years, 40% female; PD mean age = 70.3 ± 1.8 years, 40% female) while disease duration was significantly shorter in PSP (PSP 14 ± 3.5 months vs PD 87.9 ± 16.9 months). Gait parameters showed significant group differences with effect sizes ranging from d = 1.0 to 2.27. Gait speed was significantly slower in PSP: 0.45 ± 0.06 m/s vs. 0.79 ± 0.06 m/s in PD (d = 1.78, p < 0.001). CONCLUSION: Our study demonstrates the feasibility of measuring gait in PSP and PD remotely using wearable sensors. The study provides insight into digital biomarkers for both neurodegenerative diseases. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04753320, first posted Febuary 15, 2021.

Care4AD: A Technology-Driven Platform for Care Coordination and Management: Acceptability Study in Dementia.

INTRODUCTION: The technology-driven solution can reduce the caregiving burden; however, the needs of dementia caregiving are unique, and attitudes towards adopting technology from the perspectives of all the stakeholders involved in dementia caregiving are unclear. This study aims to assess the acceptability and feasibility of a technology-driven platform to facilitate care coordination platform, Care4AD, from the end-user perspective. METHODS: Care4AD includes three components: (1) Care4AD app: the app is used by caregivers to coordinate care, monitor physical activity, and schedule reminders; (2) Care4AD tablet: a smart tablet is used by the care recipient to display scheduled reminders; and (3) Care4AD tags: a series of wireless sensor tags attached to various objects of daily care to facilitate monitoring instrumental activities of daily living (IADL) and adherence to scheduled tasks. Stakeholders in caregiving, including 11 experts in dementia care (age: 53.3 ± 8, 73% female), 10 individuals with dementia (IWD) (age: 76.1 ± 7.3, 50% female), and 14 caregivers (age: 66.9 ± 10.6, 75% female) were interviewed to determine perceived ease of use, attitude towards use, and perceived usefulness, based on the technology acceptance model (TAM) questionnaire. Additionally, we assessed technology anxiety and concerns with data sharing by caregivers and IWD. The interviews were conducted through videoconferencing or in-person meetings. The interview was composed of open-ended questions, a demonstration of the proposed Care4AD platform, and a survey based on TAM. RESULTS: Compared to the neutral response, stakeholders showed significantly higher acceptance (70-100% satisfied to highly satisfied, p < 0.05) for all components of the TAM. Among IWD, age (r = -0.68, p = 0.03) and for caregivers the perceived ease of use (r = 0.73, p < 0.01) were significant predictors of attitude towards using the technology. Interestingly, neither concerns about data sharing nor educational level were limiting factors in the acceptability of the system in our sample. CONCLUSION: Overall, the results support a high perception of usefulness, ease of use, and attitude towards using Care4AD. The key barriers to adopting such technology are the age of IWD and the caregiver's perception of ease of use. Future studies are warranted to explore the effectiveness of such a platform to reduce caregiver stress and improve the quality of life and independence of IWD.

Machine Learning-Based Aggression Detection in Children with ADHD Using Sensor-Based Physical Activity Monitoring.

Aggression in children is highly prevalent and can have devastating consequences, yet there is currently no objective method to track its frequency in daily life. This study aims to investigate the use of wearable-sensor-derived physical activity data and machine learning to objectively identify physical-aggressive incidents in children. Participants (n = 39) aged 7 to 16 years, with and without ADHD, wore a waist-worn activity monitor (ActiGraph, GT3X+) for up to one week, three times over 12 months, while demographic, anthropometric, and clinical data were collected. Machine learning techniques, specifically random forest, were used to analyze patterns that identify physical-aggressive incident with 1-min time resolution. A total of 119 aggression episodes, lasting 7.3 ± 13.1 min for a total of 872 1-min epochs including 132 physical aggression epochs, were collected. The model achieved high precision (80.2%), accuracy (82.0%), recall (85.0%), F1 score (82.4%), and area under the curve (89.3%) to distinguish physical aggression epochs. The sensor-derived feature of vector magnitude (faster triaxial acceleration) was the second contributing feature in the model, and significantly distinguished aggression and non-aggression epochs. If validated in larger samples, this model could provide a practical and efficient solution for remotely detecting and managing aggressive incidents in children.

Evaluation of Motor and Cognitive Performance in People with Parkinson's Disease Using Instrumented Trail-Making Test.

INTRODUCTION: Parkinson's disease (PD) progressively impairs motor and cognitive performance. The current tools to detect decline in motor and cognitive functioning are often impractical for busy clinics and home settings. To address the gap, we designed an instrumented trail-making task (iTMT) based on a wearable sensor (worn on the shin) with interactive game-based software installed on a tablet. The iTMT test includes reaching to 5 indexed circles, a combination of numbers (1-3) and letters (A&B) randomly positioned inside target circles, in a sequential order, which virtually appears on a screen kept in front of the participants, by rotating one's ankle joint while standing and holding a chair for safety. By measuring time to complete iTMT task (iTMT time), iTMT enables quantifying cognitive-motor performance. PURPOSE: This study's objective is to examine the feasibility of iTMT to detect early cognitive-motor decline in PDs. METHOD: Three groups of volunteers, including 14 cognitively normal (CN) older adults, 14 PDs, and 11 mild cognitive impaireds (MCI), were recruited. Participants completed MoCA, 20 m walking test, and 3 trials of iTMT. RESULTS: All participants enabled to complete iTMT with <3 min, indicating high feasibility. The average iTMT time for CN-Older, PD, and MCI participants were 20.9 ± 0.9 s, 32.3 ± 2.4 s, and 40.9 ± 4.5 s, respectively. After adjusting for age and education level, pairwise comparison suggested large effect sizes for iTMT between CN-older versus PD (Cohen's d = 1.7, p = 0.024) and CN-older versus MCI (d = 1.57, p < 0.01). Significant correlations were observed when comparing iTMT time with the gait speed (r = -0.4, p = 0.011) and MoCA score (r = -0.56, p < 0.01). CONCLUSION: This study demonstrated the feasibility and early results supporting the potential application of iTMT to determine cognitive-motor and distinguishing individuals with MCI and PD from CN-older adults. Future studies are warranted to test the ability of iTMT to track its subtle changes over time.

Using Wearable Sensors to Measure Goal Achievement in Older Veterans with Dementia.

Aligning treatment with patients' self-determined goals and health priorities is challenging in dementia care. Wearable-based remote health monitoring may facilitate determining the active participation of individuals with dementia towards achieving the determined goals. The present study aimed to demonstrate the feasibility of using wearables to assess healthcare goals set by older adults with cognitive impairment. We present four specific cases that assess (1) the feasibility of using wearables to monitor healthcare goals, (2) differences in function after goal-setting visits, and (3) goal achievement. Older veterans (n = 17) with cognitive impairment completed self-report assessments of mobility, then had an audio-recorded encounter with a geriatrician and wore a pendant sensor for 48 h. Follow-up was conducted at 4-6 months. Data obtained by wearables augments self-reported data and assessed function over time. Four patient cases illustrate the utility of combining sensors, self-report, notes from electronic health records, and visit transcripts at baseline and follow-up to assess goal achievement. Using data from multiple sources, we showed that the use of wearable devices could support clinical communication, mainly when patients, clinicians, and caregivers work to align care with the patient's priorities.

Objective Assessment of Upper-Extremity Motor Functions in Spinocerebellar Ataxia Using Wearable Sensors.

The study presents a novel approach to objectively assessing the upper-extremity motor symptoms in spinocerebellar ataxia (SCA) using data collected via a wearable sensor worn on the patient's wrist during upper-extremity tasks associated with the Assessment and Rating of Ataxia (SARA). First, we developed an algorithm for detecting/extracting the cycles of the finger-to-nose test (FNT). We extracted multiple features from the detected cycles and identified features and parameters correlated with the SARA scores. Additionally, we developed models to predict the severity of symptoms based on the FNT. The proposed technique was validated on a dataset comprising the seventeen (n = 17) participants' assessments. The cycle detection technique showed an accuracy of 97.6% in a Bland-Altman analysis and a 94% accuracy (F1-score of 0.93) in predicting the severity of the FNT. Furthermore, the dependency of the upper-extremity tests was investigated through statistical analysis, and the results confirm dependency and potential redundancies in the upper-extremity SARA assessments. Our findings pave the way to enhance the utility of objective measures of SCA assessments. The proposed wearable-based platform has the potential to eliminate subjectivity and inter-rater variabilities in assessing ataxia.

Smart-Home Concept for Remote Monitoring of Instrumental Activities of Daily Living (IADL) in Older Adults with Cognitive Impairment: A Proof of Concept and Feasibility Study.

Assessment of instrumental activities of daily living (IADL) is essential for the diagnosis and staging of dementia. However, current IADL assessments are subjective and cannot be administered remotely. We proposed a smart-home design, called IADLSys, for remote monitoring of IADL. IADLSys consists of three major components: (1) wireless physical tags (pTAG) attached to objects of interest, (2) a pendant-sensor to monitor physical activities and detect interaction with pTAGs, and (3) an interactive tablet as a gateway to transfer data to a secured cloud. Four studies, including an exploratory clinical study with five older adults with clinically confirmed cognitive impairment, who used IADLSys for 24 h/7 days, were performed to confirm IADLSys feasibility, acceptability, adherence, and validity of detecting IADLs of interest and physical activity. Exploratory tests in two cases with severe and mild cognitive impairment, respectively, revealed that a case with severe cognitive impairment either overestimated or underestimated the frequency of performed IADLs, whereas self-reporting and objective IADL were comparable for the case with mild cognitive impairment. This feasibility and acceptability study may pave the way to implement the smart-home concept to remotely monitor IADL, which in turn may assist in providing personalized support to people with cognitive impairment, while tracking the decline in both physical and cognitive function.

Using Wearable Sensors and Machine Learning to Assess Upper Limb Function in Huntington's Disease.

Huntington's disease (HD), like many other neurological disorders, affects both lower and upper limb function that is typically assessed in the clinic - providing a snapshot of disease symptoms. Wearable sensors enable the collection of real-world data that can complement such clinical assessments and provide a more comprehensive insight into disease symptoms. In this context, almost all studies are focused on assessing lower limb function via monitoring of gait, physical activity and ambulation. In this study, we monitor upper limb function during activities of daily living in individuals with HD (n = 16), prodromal HD (pHD, n = 7), and controls (CTR, n = 16) using a wrist-worn wearable sensor, called PAMSys ULM, over seven days. The participants were highly compliant in wearing the sensor with an average daily compliance of 99% (100% for HD, 98% for pHD, and 99% for CTR). Goal-directed movements (GDM) of the hand were detected using a deep learning model, and kinematic features of each GDM were estimated. The collected data was used to predict disease groups (i.e., HD, pHD, and CTR) and clinical scores using a combination of statistical and machine learning-based models. Significant differences in GDM features were observed between the groups. HD participants performed fewer GDMs with long duration (> 7.5 seconds) compared to CTR (p-val = 0.021, d = -0.86). In velocity and acceleration metrics, the highest effect size feature was the entropy of the velocity zero-crossing length segments (HD vs CTR p-val <0.001, d = -1.67; HD vs pHD p-val = 0.043, d=-0.98; CTR vs pHD p-val = 0.046, d=0.96). In addition, this same variable showed a strongest correlation with clinical scores. Classification models achieved good performance in distinguishing HD, pHD and CTR individuals with a balanced accuracy of 67% and a 0.72 recall for the HD group, while regression models accurately predicted clinical scores. Notably the explained variance for the upper extremity function subdomain scale of Unified Huntington's Disease Rating Scale (UHDRS) was the highest, with the model capturing 60% of the variance. Our findings suggest the potential of wearables and machine learning for early identification of phenoconversion, remote monitoring in HD, and evaluating new treatments efficacy in clinical trials and medicine.

Digital assessment of speech in Huntington disease.

Background: Speech changes are an early symptom of Huntington disease (HD) and may occur prior to other motor and cognitive symptoms. Assessment of HD commonly uses clinician-rated outcome measures, which can be limited by observer variability and episodic administration. Speech symptoms are well suited for evaluation by digital measures which can enable sensitive, frequent, passive, and remote administration. Methods: We collected audio recordings using an external microphone of 36 (18 HD, 7 prodromal HD, and 11 control) participants completing passage reading, counting forward, and counting backwards speech tasks. Motor and cognitive assessments were also administered. Features including pausing, pitch, and accuracy were automatically extracted from recordings using the BioDigit Speech software and compared between the three groups. Speech features were also analyzed by the Unified Huntington Disease Rating Scale (UHDRS) dysarthria score. Random forest machine learning models were implemented to predict clinical status and clinical scores from speech features. Results: Significant differences in pausing, intelligibility, and accuracy features were observed between HD, prodromal HD, and control groups for the passage reading task (e.g., p < 0.001 with Cohen'd = -2 between HD and control groups for pause ratio). A few parameters were significantly different between the HD and control groups for the counting forward and backwards speech tasks. A random forest classifier predicted clinical status from speech tasks with a balanced accuracy of 73% and an AUC of 0.92. Random forest regressors predicted clinical outcomes from speech features with mean absolute error ranging from 2.43-9.64 for UHDRS total functional capacity, motor and dysarthria scores, and explained variance ranging from 14 to 65%. Montreal Cognitive Assessment scores were predicted with mean absolute error of 2.3 and explained variance of 30%. Conclusion: Speech data have the potential to be a valuable digital measure of HD progression, and can also enable remote, frequent disease assessment in prodromal HD and HD. Clinical status and disease severity were predicted from extracted speech features using random forest machine learning models. Speech measurements could be leveraged as sensitive marker of clinical onset and disease progression in future clinical trials.

A deep learning wearable-based solution for continuous at-home monitoring of upper limb goal-directed movements.

Introduction: Monitoring upper limb function is crucial for tracking progress, assessing treatment effectiveness, and identifying potential problems or complications. Hand goal-directed movements (GDMs) are a crucial aspect of daily life, reflecting planned motor commands with hand trajectories towards specific target locations. Previous studies have shown that GDM tasks can detect early changes in upper limb function in neurodegenerative diseases and can be used to track disease progression over time. Methods: In this study, we used accelerometer data from stroke survivor participants and controls doing activities of daily living to develop an automated deep learning approach to detect GDMs. The model performance for detecting GDM or non-GDM from windowed data achieved an AUC of 0.9, accuracy 0.83, sensitivity 0.81, specificity 0.84 and F1 0.82. Results: We further validated the utility of detecting GDM by extracting features from GDM periods and using these features to classify whether the measurements are collected from a stroke survivor or a control participant, and to predict the Fugl-Meyer assessment score from stroke survivors. Discussion: This study presents a promising and reliable tool for monitoring upper limb function in a real-world setting, and assessing biomarkers related to upper limb health in neurological, neuromuscular and muscles disorders.

Objective assessment of mobility among adults with diabetes and end-stage renal disease using walking aid: A cross-sectional cohort study.

BACKGROUND: This cross-sectional study aimed to compare physical activity levels, plantar sensation, and fear of falling between individuals with diabetes undergoing hemodialysis, with or without walking aids. METHODS: Sixty-four participants were recruited, with 37 not using walking aids (age = 65.8 ± 0.7 years, 46% female) and 27 using walking aids (age = 69.2 ± 1.2 years, 63% female). Physical activity was measured using validated pendant sensors over two consecutive days. Concern for falling and plantar numbness were assessed using the Falls Efficacy Scale-International and vibration perception threshold test, respectively. FINDINGS: Participants using walking aids exhibited a greater fear of falling (84% vs. 38%, p < 0.01) and fewer walking bouts (p < 0.01, d = 0.67) and stand-to-walk transitions (p < 0.01, d = 0.72) compared to those not using walking aids. The number of walking bouts was negatively correlated with concern for falling scores (ρ = -0.35, p = 0.034) and vibration perception threshold (R = -0.411, p = 0.012) among individuals not using walking aids. However, these correlations were not significant among those using the walking aid. There was no significant group difference in active behavior (walking + standing %) and sedentary behavior (sitting + lying %). INTERPRETATION: Those undergoing hemodialysis often lead sedentary lives, with mobility affected by fear of falling and plantar numbness. Using walking aids can help, but it doesn't guarantee more walking. A combined psychosocial and physical therapy approach is key for managing fall concerns and improving mobility.

Intradialytic plantar electrical nerve stimulation to improve mobility and plantar sensation among adults with diabetes undergoing hemodialysis: a randomized double-blind trial.

BACKGROUND: Impaired mobility is a debilitating consequence of hemodialysis. We examined the efficacy of intradialytic-plantar-electrical-nerve-stimulation (iPENS) to promote mobility among diabetes patients undergoing hemodialysis.. METHODS: Adults with diabetes undergoing hemodialysis received either 1-h active iPENS, (Intervention-Group) or non-functional iPENS (Control-Group) during routine hemodialysis for 12 weeks (3 sessions/week). Participants and care-providers were blinded. Mobility (assessed using a validated pendant-sensor) and neuropathy (quantified by vibration-perception-threshold test) outcomes were assessed at baseline and 12 weeks. RESULTS: Among 77 enrolled subjects (56.2 ± 2.6 years old), 39 were randomly assigned to the intervention group, while 38 were assigned to the control group. No study-related adverse events and dropouts were reported in the intervention group. Compared to the control group, significant improvements with medium to large effect sizes were observed in the intervention group at 12 weeks for mobility-performance metrics, including active-behavior, sedentary-behavior, daily step counts, and sit-to-stand duration variability (p < 0.05), Cohen's d effect size (d = 0.63-0.84). The magnitude of improvement in active-behavior was correlated with improvement in the vibration-perception-threshold test in the intervention group (r = - 0.33, p = 0.048). A subgroup with severe-neuropathy (vibration-perception-threshold > 25 V) showed a significant reduction in plantar numbness at 12 weeks compared to baseline (p = 0.03, d = 1.1). CONCLUSIONS: This study supports feasibility, acceptability, and effectiveness of iPENS to improve mobility and potentially reduce plantar numbness in people with diabetes undergoing hemodialysis. Considering that exercise programs are not widely used in hemodialysis clinical practice, iPENS may serve as a practical, alternative solution to reduce hemodialysis-acquired weakness and promote mobility.

Utilizing speech analysis to differentiate progressive supranuclear palsy from Parkinson's disease.

INTRODUCTION: Distinguishing Parkinson's disease (PD) from Progressive supranuclear palsy (PSP) at early disease stages is important for clinical trial enrollment and clinical care/prognostication. METHODS: We recruited 21 participants with PSP(n = 11) or PD(n = 10) with reliable caregivers. Standardized passage reading, counting, and sustained phonation were recorded on the BioDigit Home tablet (BioSensics LLC, Newton, MA USA), and speech features from the assessments were analyzed using the BioDigit Speech platform (BioSensics LLC, Newton, MA USA). An independent t-test was performed to compare each speech feature between PSP and PD participants. We also performed Spearman's correlations to evaluate associations between speech measures and clinical scores (e.g., PSP rating scales and MoCA). In addition, the model's performance in classifying PSP and PD was evaluated using Rainbow passage reading analysis. RESULTS: During Rainbow passage reading, PSP participants had a significantly slower articulation rate (2.45(0.49) vs 3.60(0.47) words/minute), lower speech-to-pause ratio (2.33(1.08) vs 3.67(1.18)), intelligibility dynamic time warping (DTW, 0.26(0.19) vs 0.53(0.26)), and similarity DTW (0.43(0.27) vs 0.67(0.13)) compared to PD participants. PSP participants also had longer pause times (17.24(5.47) vs 8.45(3.13) sec) and longer total signal times (52.44(6.67) vs (36.67(6.73) sec) when reading the passage. In terms of the phonation 'a', PSP participants showed a significant higher spectral entropy, spectral centroid, and spectral spread compared to PD participants and no differences were found for phonation 'e'. PD participants had more accurate reverse number counts than PSP participants (14.89(3.86) vs 7.36(4.67)). PSP Rating Scale (PSPRS) dysarthria (r = 0.79, p = 0.004) and bulbar item scores (r = 0.803, p = 0.005) were positively correlated with articulation rate in reverse number counts. Correct reverse number counts were positively correlated with total Montreal Cognitive Assessment scores (r = 0.703, p = 0.016). Machine learning models using passage reading-derived measures obtained an AUC of 0.93, and the sensitivity/specificity in correctly classifying PSP and PD participants were 0.95 and 0.90, respectively. CONCLUSION: Our study demonstrates the feasibility of differentiating PSP from PD using a digital health technology platform. Further multi-center studies are needed to expand and validate our initial findings.

Effect of concurrent transcranial direct current stimulation on instrumented timed up and go task performance in people with Parkinson's disease: A double-blind and cross-over study.

Transcranial direct current stimulation (tDCS) delivered to the dorsolateral prefrontal cortex (DLPFC) can improve mobility among people with Parkinson's disease (PD). Previous studies suggest that delivering tDCS during task performance might be beneficial. However, only a few studies explored the effect of combining tDCS with task. We investigated the effect of stimulating the DLPFC using anodal tDCS while performing a timed up and go (TUG) test and its sustained effects. In this sham-controlled, cross-over, and double-blind study, twenty participants with PD (age = 67.8 ± 8.3 years and 6 females) completed two sessions (anodal or sham tDCS), conducted in the randomized and counterbalanced manner, with at least a 1-week gap. Stimulation involved transferring 2 mA current through the DLPFC for 30 min. Single-trial of TUG test was performed under single- and dual-task conditions before, during, immediately after, 15 and 30 min after stimulation ceased. We estimated durations of completing different components of TUG. Phoneme verbal fluency task was given as the cognitive distractor during the dual-tasking. An improvement was observed in cognitive performance due to the tDCS condition (d = 0.7, p < 0.01) over time. However, we found no effect of tDCS condition on iTUG related outcomes under single- or dual-task conditions. In conclusion, DLPFC stimulation combined with task improved cognitive performance only, and the improvement was sustained after tDCS ceased. Future studies may investigate stimulating multiple brain regions to improve motor and cognitive performance.

The Application of Digital Frailty Screening to Triage Nonhealing and Complex Wounds.

OBJECTIVE: We investigated the association between the complexity of diabetic foot ulcers (DFUs) and frailty. RESEARCH DESIGN AND METHODS: Individuals (n = 38) with Grade 2 Wagner DFU were classified into 3 groups based on the Society for Vascular Surgery risk-stratification for major limb amputation as Stage 1 at very low risk (n = 19), Stage 2 at low risk (n = 9), and Stage 3 to 4 at moderate-to-high risk (n = 10) of major limb amputation. Frailty status was objectively assessed using a validated digital frailty meter (FM). The FM works by quantifying weakness, slowness, rigidity, and exhaustion over a 20-second repetitive elbow flexion-extension exercise using a wrist-worn sensor. FM generates a frailty index (FI) ranging from 0 to 1; higher values indicate progressively greater severity of frailty. Skin perfusion pressure (SPP), albumin, and tissue oxygenation level (SatO2) were also measured. One-way analysis of variance (ANOVA) was used to identify group effect for wound complexity. Pearson's correlation coefficient was used to assess the associations with frailty and clinical endpoints. RESULTS: Frailty index was higher in Stage 3 and 4 as compared to Stage 1 (d = 1.4, P < .01) and Stage 2 (d = 1.2, P < .01). Among assessed frailty phenotypes, exhaustion was correlated with SPP (r = -0.63, P < .01) and albumin (r = -0.5, P < .01). CONCLUSION: Digital biomarkers of frailty may predict complexity of DFU and thus triage individuals who can be treated more simply in their primary clinic versus higher risk patients who require prompt referral to multidisciplinary, more complex care.

Tele-Medicine Based and Self-Administered Interactive Exercise Program (Tele-Exergame) to Improve Cognition in Older Adults with Mild Cognitive Impairment or Dementia: A Feasibility, Acceptability, and Proof-of-Concept Study.

Improved life expectancy is increasing the number of older adults who suffer from motor-cognitive decline. Unfortunately, conventional balance exercise programs are not tailored to patients with cognitive impairments, and exercise adherence is often poor due to unsupervised settings. This study describes the acceptability and feasibility of a sensor-based in-home interactive exercise system, called tele-Exergame, used by older adults with mild cognitive impairment (MCI) or dementia. Our tele-Exergame is specifically designed to improve balance and cognition during distractive conditioning while a telemedicine interface remotely supervises the exercise, and its exercises are gamified balance tasks with explicit augmented visual feedback. Fourteen adults with MCI or dementia (Age = 68.1 ± 5.4 years, 12 females) participated and completed exergame twice weekly for six weeks at their homes. Before and after 6 weeks, participants' acceptance was assessed by Technology Acceptance Model (TAM) questionnaire, and participants' cognition and anxiety level were evaluated by the Montreal Cognitive Assessment (MoCA) and Beck Anxiety Inventory (BAI), respectively. Results support acceptability, perceived benefits, and positive attitudes toward the use of the system. The findings of this study support the feasibility, acceptability, and potential benefit of tele-Exergame to preserve cognitive function among older adults with MCI and dementia.

Transcranial direct current stimulation of dorsolateral prefrontal cortex improves dual-task gait performance in patients with Parkinson's disease: A double blind, sham-controlled study.

BACKGROUND: Despite advances in pharmacological treatments and surgical processes, the problem of impaired dual-tasking persists in people with Parkinson's disease (PD). Recently, transcranial direct current stimulation (tDCS) applied to the dorsolateral prefrontal cortex (DLPFC) has shown the potential to improve dual-task walking. RESEARCH QUESTION: Can combining left DLPFC stimulation using tDCS with dual-task performance reduce the cost of dual-tasking in individuals with PD? METHODS: We conducted a sham-controlled, cross-over, and double-blind study to investigate the effect of combining tDCS with the dual-task walk and its sustained effects among people with PD. Twenty participants with PD completed two sessions (anodal or sham tDCS) with at least a 1-week gap. Stimulation involved transferring 2 mA current through the left DLPFC for 30 min. Single- and dual-task gait was assessed before, during, immediately after, 15, and 30 min after stimulation ceased. Phoneme verbal fluency task was given as the cognitive distractor during dual task. RESULTS AND CONCLUSION: The results of this study show that in the dual-task condition, participants walked faster at fifteen minutes (p = 0.017) and thirty minutes (p < 0.01) after anodal tDCS ceased compared to sham. Similarly, participants generated a higher number of words per minute at fifteen minutes (p = 0.017), and thirty minutes (p < 0.01) after anodal tDCS ceased compared to sham. Furthermore, the dual-task cost (DTC) associated with gait speed was significantly lower (p = 0.022) at fifteen minutes after anodal tDCS compared to sham tDCS. However, no significant effect of tDCS was observed on gait and cognitive performance under the single-task condition. In conclusion, left DLPFC stimulation can improve dual-tasking in participants with PD and the peaking of the tDCS effect was observed at fifteen minutes after stimulation ceased.