A wearable inertial system to evaluate Tai Chi training motor effects in patients with Parkinson's disease.

Physical therapy is strongly recommended for patients with neurological disorders. Tai Chi-based treatments seem to improve physical functions like gait speed and balance. However, assessments after treatment rely on semi-quantitative clinical scales affected by subjectivity with controversial results. This study aims at investigating whether Tai Chi could be a valid alternative to traditional physiotherapy rehabilitation. We propose a wearable system composed of two inertial devices able to objectively measure the effect of the rehabilitation treatment on the range of movement of the trunk. Seventeen patients with Parkinson's Disease (PD) were recruited and assessed. They have been randomly divided into two groups: group 1 followed a Tai Chi-based treatment, while group 2 underwent a traditional physiotherapy rehabilitation. The two groups have been assessed before (t0) and after the treatment (t1). No statistical differences have been found in the relative range of motion between the upper and lower sensors between the two groups at the baseline. Both treatments resulted in a significant improvement in the trunk range of movement (on the right side). Notably, the improvement in the effect size of the treatment was greater in group 1 than in group 2. In fact, even if both the groups benefited from their treatment group 1 gained larger mobility of the trunk if compared to group 2. Interestingly, no differences have been accounted adopting the traditional UPDRS III for motor symptoms of PD, strengthening the idea that objective measurement coming from wearable biomedical sensors could detect information otherwise neglected by traditional clinical tools.Clinical Relevance- This study preliminary confirms that beneficial motor effects after a Tai Chi rehabilitation program are comparable and quite better than after traditional physiotherapy, promoting Tai Chi as a valid alternative treatment for PD patients.

Mild cognitive impairment identification based on motor and cognitive dual-task pooled indices.

OBJECTIVE: This study investigates the possibility of adopting motor and cognitive dual-task (MCDT) approaches to identify subjects with mild cognitive impairment (MCI) and subjective cognitive impairment (SCI). METHODS: The upper and lower motor performances of 44 older adults were assessed using the SensHand and SensFoot wearable system during three MCDTs: forefinger tapping (FTAP), toe-tapping heel pin (TTHP), and walking 10 m (GAIT). We developed five pooled indices (PIs) based on these MCDTs, and we included them, along with demographic data (age) and clinical scores (Frontal Assessment Battery (FAB) scores), in five logistic regression models. RESULTS: Models which consider cognitively normal adult (CNA) vs MCI subjects have accuracies that range from 67% to 78%. The addition of clinical scores stabilised the accuracies, which ranged from 85% to 89%. For models which consider CNA vs SCI vs MCI subjects, there are great benefits to considering all three regressors (age, FAB score, and PIs); the overall accuracies of the three-class models range between 50% and 59% when just PIs and age are considered, whereas the overall accuracy increases by 18% when all three regressors are utilised. CONCLUSION: Logistic regression models that consider MCDT PIs and age have been effective in distinguishing between CNA and MCI subjects. The inclusion of clinical scores increased the models' accuracy. Particularly high performances in distinguishing among CNA, SCI, and MCI subjects were obtained by the TTHP PI. This study suggests that a broader framework for MCDTs, which should encompass a greater selection of motor tasks, could provide clinicians with new appropriate tools.

User Profiling to Enhance Clinical Assessment and Human-Robot Interaction: A Feasibility Study.

Socially Assistive Robots (SARs) are designed to support us in our daily life as a companion, and assistance but also to support the caregivers' work. SARs should show personalized and human-like behavior to improve their acceptance and, consequently, their use. Additionally, they should be trustworthy by caregivers and professionals to be used as support for their work (e.g. objective assessment, decision support tools). In this context the aim of the paper is dual. Firstly, this paper aims to present and discuss the robot behavioral model based on sensing, perception, decision support, and interaction modules. The novel idea behind the proposed model is to extract and use the same multimodal features set for two purposes: (i) to profile the user, so to be used by the caregiver as a decision support tool for the assessment and monitoring of the patient; (ii) to fine-tune the human-robot interaction if they can be correlated to the social cues. Secondly, this paper aims to test in a real environment the proposed model using a SAR robot, namely ASTRO. Particularly, it measures the body posture, the gait cycle, and the handgrip strength during the walking support task. Those collected data were analyzed to assess the clinical profile and to fine-tune the physical interaction. Ten older people (65.2 ± 15.6 years) were enrolled for this study and were asked to walk with ASTRO at their normal speed for 10 m. The obtained results underline a good estimation (p < 0.05) of gait parameters, handgrip strength, and angular excursion of the torso with respect to most used instruments. Additionally, the sensory outputs were combined in the perceptual model to profile the user using non-classical and unsupervised techniques for dimensionality reduction namely T-distributed Stochastic Neighbor Embedding (t-SNE) and non-classic multidimensional scaling (nMDS). Indeed, these methods can group the participants according to their residual walking abilities.

A New Motor and Cognitive Dual-Task Approach Based on Foot Tapping for The Identification of Mild Cognitive Impairment.

This study investigates the adoption of innovative Motor and Cognitive Dual-Task (MCDT) based on the combination of increasing motor and cognitive tasks to discern between subjects with Mild Cognitive Impairment (MCI) and Cognitively Normal Adults (CNA). We aim to adopt new MCDT protocols and to compare their performance against the gold standard (a walking based MCDT, called GAIT). 27 older adults have been assessed through a customized wearable system during 4 MCDTs. We developed as many pooled indices (PIs), based on MCDTs perfomance, demographic data, and clinical scores. We use these parameters as regressors in 4 different logistic regression models. The regression models that encompassed features from innovative MCDT overcame the gold standard classification performance. In particular, models based on the heel tapping and the alternate heel-toe tapping reach the best outputs, namely +8% of accuracy if compared to the gold standard (a walking task). The use of logistic regression models based on MCDT PI have been effective in discerning between CNA vs MCI. Our results suggest that the gold standard MCDT may represents a too demanding exercise to highlight differences between CNA and MCI. It seems that MCDT based on an intermediate level of motor difficulty could represent the sweet spot for the identification of MCI against CNA. Clinical relevance- The combination of innovative digital devices and innovative approach on data analysis (PIs) opened a new scenarios to the early detection and prediction of dementia. Their use would standardize the assessment procedure, lightening the physician from the burden of cumbersome testing sessions. This study suggests that a broader framework for MCDT, which should encompass an ampler selection of motor tasks with different possibilities in terms of difficulties levels, could provide clinicians with a new appropriate set of tools for the early detection of dementia.

Personalizing Care Through Robotic Assistance and Clinical Supervision.

By 2030, the World Health Organization (WHO) foresees a worldwide workforce shortfall of healthcare professionals, with dramatic consequences for patients, economies, and communities. Research in assistive robotics has experienced an increasing attention during the last decade demonstrating its utility in the realization of intelligent robotic solutions for healthcare and social assistance, also to compensate for such workforce shortages. Nevertheless, a challenge for effective assistive robots is dealing with a high variety of situations and contextualizing their interactions according to living contexts and habits (or preferences) of assisted people. This study presents a novel cognitive system for assistive robots that rely on artificial intelligence (AI) representation and reasoning features/services to support decision-making processes of healthcare assistants. We proposed an original integration of AI-based features, that is, knowledge representation and reasoning and automated planning to 1) define a human-in-the-loop continuous assistance procedure that helps clinicians in evaluating and managing patients and; 2) to dynamically adapt robot behaviors to the specific needs and interaction abilities of patients. The system is deployed in a realistic assistive scenario to demonstrate its feasibility to support a clinician taking care of several patients with different conditions and needs.

A wearable ring-shaped inertial system to identify action planning impairments during reach-to-grasp sequences: a pilot study.

BACKGROUND: The progressive ageing of the population is leading to an increasing number of people affected by cognitive decline, including disorders in executive functions (EFs), such as action planning. Current procedures to evaluate cognitive decline are based on neuropsychological tests, but novel methods and approaches start to be investigated. Reach-to-grasp (RG) protocols have shown that intentions can influence the EFs of action planning. In this work, we proposed a novel ring-shaped wearable inertial device, SensRing, to measure kinematic parameters during RG and after-grasp (AG) tasks with different end-goals. The aim is to evaluate whether SensRing can characterize the motor performances of people affected by Mild Neurocognitive Disorder (MND) with impairment in EFs. METHODS: Eight Individuals with dysexecutive MND, named d-MND, were compared to ten older healthy subjects (HC). They were asked to reach and grasp a can with three different intentions: to drink (DRINK), to place it on a target (PLACE), or to pass it to a partner (PASS). Twenty-one kinematic parameters were extracted from SensRing inertial data. RESULTS: Seven parameters resulted able to differentiate between HC and d-MND in the RG phase, and 8 features resulted significant in the AG phase. d-MND, indeed, had longer reaction times (in RG PLACE), slower peak velocities (in RG PLACE and PASS, in AG DRINK and PLACE), longer deceleration phases (in all RG and AG DRINK), and higher variability (in RG PLACE, in AG DRINK and PASS). Furthermore, d-MND showed no significant differences among conditions, suggesting that impairments in EFs influence their capabilities in modulating the action planning based on the end-goal. CONCLUSIONS: Based on this explorative study, the system might have the potential for objectifying the clinical assessment of people affected by d-MND by administering an easy motor test. Although these preliminary results have to be investigated in-depth in a larger sample, the portability, wearability, accuracy, and ease-of use of the system make the SensRing potentially appliable for remote applications at home, including analysis of protocols for neuromotor rehabilitation in patients affected by MND.

Grasping Social Apathy: The Role of Reach-To-Grasp Action Kinematics for the Assessment of Social Apathy in Mild Neurocognitive Disorders.

BACKGROUND: Social apathy, a reduction in initiative in proposing or engaging in social activities or interactions, is common in mild neurocognitive disorders (MND). Current apathy assessment relies on self-reports or clinical scales, but growing attention is devoted to defining more objective, measurable and non-invasive apathy proxies. OBJECTIVE: In the present study we investigated the interest of recording action kinematics in a social reach-to-grasp task for the assessment of social apathy. METHODS: Thirty participants took part in the study: 11 healthy controls (HC; 6 females, mean age = 68.3±10.5 years) and 19 subjects with MND (13 females, mean age = 75.7±6.3 years). Based on the Diagnostic Criteria for Apathy, MND subjects were classified as socially apathetic (A-MND, N = 9) versus non-apathetic (NA-MND, N = 10). SensRing, a ring-shaped wearable sensor, was placed on their index finger, and subjects were asked to reach and grasp a can to place it into a cup (individual condition) and pass it to a partner (social condition). RESULTS: In the reach-to-grasp phase of the action, HC and NA-MND showed different acceleration and velocity profiles in the social versus individual condition. No differences were found for A-MND. CONCLUSION: Previous studies showed the interest of recording patients' level of weekly motor activity for apathy assessment. Here we showed that a 10-min reach-to-grasp task may provide information to differentiate socially apathetic and non-apathetic subjects with MND, thus providing a tool easily usable in the clinical practice. Future studies with a bigger sample are needed to better characterize these findings.

Innovative motor and cognitive dual-task approaches combining upper and lower limbs may improve dementia early detection.

Motor and Cognitive Dual-Task (MCDT) represents an innovative chance to assess Mild Cognitive Impairment (MCI). We compare two novel MCDTs, fore-finger tapping (FTAP), toe-tapping (TTHP), to gold standards for cognitive screening (Mini-Mental State Examination-MMSE), and to a well-established MCDT (GAIT). We administered the aforementioned MCDTs to 44 subjects (MCIs and controls). Motor parameters were extracted, and correlations with MMSE investigated. Logistic regression models were built, and AUC areas computed. Spearman's correlation demonstrated that FTAP and TTHP significantly correlate with MMSE, at each cognitive load. AUC areas computed report similar (FTAP, 0.87), and even higher (TTHP, 0.97) capability to identify MCIs, if compared to GAIT (0.92). We investigated the use of novel MCDT approaches to assess MCI, aiming to enrich the clinical repertoire with objective and non-invasive tools. Our protocol shows good correlations with MMSE, and reaches high performances in identifying MCI, adopting simpler exercises.

The use of Motor and Cognitive Dual-Task quantitative assessment on subjects with mild cognitive impairment: A systematic review.

Dementia and Alzheimer's Disease (AD) represent a health emergency. The identification of valid and noninvasive markers to identify people with Mild Cognitive Impairment (MCI) is profoundly advocated. This review outlines the use of quantitative Motor and Cognitive Dual-Task (MCDT) on MCI, by technologies aid. We describe the framework and the most valuable researches, displaying the adopted protocols, and the available technologies. PubMed Central, Web of Science, and Scopus were inspected between January 2010 and May 2020. 1939 articles were found in the initial quest. Exclusion criteria allowed the selection of the most relevant papers; 38 papers were included. The articles, regarding four technological solutions "wearable sensors", "personal devices", "optokinetic systems", and "electronic walkways", are organized into three categories: "Quantitative MCDT", "MCDT Inspired by Neuropsychological Test", and "MCDT for MCI Stimulation". MCDT might furnish clinical landmarks, supplying aid for disease stratication, risk prediction, and intervention optimization. Such protocols could foster the use of data mining and machine learning techniques. Notwithstanding, there is still a need to standardize and harmonize such protocols.

Novel Technological Solutions for Assessment, Treatment, and Assistance in Mild Cognitive Impairment.

Alzheimer's disease, and dementia, represent a common cause of disability and one of the most relevant challenges in the health world. In addition, these conditions do not have, at moment, a pharmacological treatment that can stop the pathological progress. Mild cognitive impairment (MCI), defined as the borderline between normal aging and early dementia, represents a meaningful field of study because, in the transition to dementia, clinicians have defined a useful therapeutic window. Additionally, due to the lack of effective pharmacological interventions, recent years have seen an increase in research into new technological solutions to assess, stimulate, and assist patients afflicted with Alzheimer's disease. This review aims to outline the use of information and communication technologies in the field studying MCI. Particularly, the goal is to depict the framework and describe the most worthwhile research efforts, in order to display the current technologies available, describe the research objectives, and delineate prospective future researches. Regarding data sources, the research was conducted within three databases, PubMed Central, Web of Science, and Scopus, between January 2009 and December 2017. A total of 646 articles were found in the initial search. Accurate definition of the exclusion criteria and selection strategy allowed identification of the most relevant papers to use for the study. Finally, 56 papers were fully evaluated and included in this review. Three major clinical application areas have been portrayed, namely "Cognitive Assessment," "Treatment," and "Assistance." These have been combined with three main technological solutions, specifically "Sensors," "Personal Devices," and "Robots." Furthermore, the study of the publications time series illustrates a steadily increasing trend, characterized by the enrollment of small groups of subjects, and particularly oriented to the subjects assistance using robots companion. In conclusion, despite the new technological solutions for people with MCI have received much interest, particularly regarding robots for assistance, nowadays it still owns vast room for improvement.

Foot Inertial Sensing for Combined Cognitive-Motor Exercise of the Sustained Attention Domain.

OBJECTIVE: In the past decade, cognitive training tools have been used to improve brain functioning, and some have been applied to cognitive decline in dementia. Recently, research studies have demonstrated that aerobic exercise could play an important restorative role toward cognitive impairments. Therefore, the main objective of this paper is to present the innovative use of the SmartWalk tool, which combines aerobic exercise and cognitive protocols traditionally used to stimulate cognitive function. METHODS: The primary goal of this study to demonstrate if our tool is correlated with traditional computerized test in stimulating the cognitive system similarly, despite the fact that SmartWalk adds a supplementary physical load on the task. The SmartWalk tool was tested with a total of 49 subjects-29 healthy subjects and 20 subjects with Mild Cognitive Impairments. The participants were asked to perform both the tests to fulfil the proposed goal. RESULTS: The results obtained considering the overall population show a good and significant (p < 0.05) correlation for the "correct," "error," and "omitted" scores (r = 0.54, r = 0.34, and r = 0.39, respectively). CONCLUSION: The results suggest a good correlation between the two approaches with the advantage of adding aerobic exercise to the traditional cognitive task. SIGNIFICANCE: The results of this study may be useful in designing ecological and combined cognitive-physical tool to personalize interventions and delay the onset of cognitive disorders like dementia.

Can physical and cognitive training based on episodic memory be combined in a new protocol for daily training?

BACKGROUND: Cognitive training (CT) is defined as guided practice on a set of standard tasks designed to stimulate particular cognitive functions. Recent studies have shown that physical exercise is beneficial for cognitive activity in older adults and patients with degenerative diseases. AIMS: The main objective of the present study is to create a new cognitive tool able to provide training for cognitive functions that take advantage of the physical activity involved in the execution of the task. A study concerning the application of a new CT tool for episodic memory is presented and divided in two parts. The first one aims at developing a new sensorized device, called SmartTapestry, for physical and cognitive training. The second part aims at understanding its technical viability and level of sensitivity in stimulating the same cognitive domain covered by the standardized tests, despite the introduction of the physical activity variable. METHODS: The SmartTapestry device was tested with a total of 53 subjects, 29 healthy subjects and 24 subjects suffering from mild cognitive impairment. RESULTS AND DISCUSSIONS: The results show a good correlation between the two approaches (p < 0.005), suggesting that SmartTapestry can stimulate the same cognitive functions of traditional cognitive tasks, with the addition of physical exercise. CONCLUSIONS: The results of this study may be useful in designing ecological and combined cognitive-physical tools, which can be used daily at home, reducing the presence of clinical staff, to train at the same time the brain and the body so as to improve the cognitive treatments efficacy.