Bibliografie tematiche / Activities of daily living recognition

Letteratura scientifica selezionata sul tema "Activities of daily living recognition"

Autore: Grafiati

Pubblicato: 8 giugno 2024

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Articoli di riviste sul tema "Activities of daily living recognition":

Wu, Jiaxuan, Yunfei Feng e Peng Sun. "Sensor Fusion for Recognition of Activities of Daily Living". Sensors 18, n. 11 (19 novembre 2018): 4029. http://dx.doi.org/10.3390/s18114029.

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Activity of daily living (ADL) is a significant predictor of the independence and functional capabilities of an individual. Measurements of ADLs help to indicate one’s health status and capabilities of quality living. Recently, the most common ways to capture ADL data are far from automation, including a costly 24/7 observation by a designated caregiver, self-reporting by the user laboriously, or filling out a written ADL survey. Fortunately, ubiquitous sensors exist in our surroundings and on electronic devices in the Internet of Things (IoT) era. We proposed the ADL Recognition System that utilizes the sensor data from a single point of contact, such as smartphones, and conducts time-series sensor fusion processing. Raw data is collected from the ADL Recorder App constantly running on a user’s smartphone with multiple embedded sensors, including the microphone, Wi-Fi scan module, heading orientation of the device, light proximity, step detector, accelerometer, gyroscope, magnetometer, etc. Key technologies in this research cover audio processing, Wi-Fi indoor positioning, proximity sensing localization, and time-series sensor data fusion. By merging the information of multiple sensors, with a time-series error correction technique, the ADL Recognition System is able to accurately profile a person’s ADLs and discover his life patterns. This paper is particularly concerned with the care for the older adults who live independently.

Ihianle, Isibor Kennedy, Usman Naeem e Abdel-Rahman Tawil. "Recognition of Activities of Daily Living from Topic Model". Procedia Computer Science 98 (2016): 24–31. http://dx.doi.org/10.1016/j.procs.2016.09.007.

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Chua, Sook-Ling, Lee Kien Foo e Hans W. Guesgen. "Predicting Activities of Daily Living with Spatio-Temporal Information". Future Internet 12, n. 12 (27 novembre 2020): 214. http://dx.doi.org/10.3390/fi12120214.

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The smart home has begun playing an important role in supporting independent living by monitoring the activities of daily living, typically for the elderly who live alone. Activity recognition in smart homes has been studied by many researchers with much effort spent on modeling user activities to predict behaviors. Most people, when performing their daily activities, interact with multiple objects both in space and through time. The interactions between user and objects in the home can provide rich contextual information in interpreting human activity. This paper shows the importance of spatial and temporal information for reasoning in smart homes and demonstrates how such information is represented for activity recognition. Evaluation was conducted on three publicly available smart-home datasets. Our method achieved an average recognition accuracy of more than 81% when predicting user activities given the spatial and temporal information.

Ortis, Alessandro, Giovanni M. Farinella, Valeria D’Amico, Luca Addesso, Giovanni Torrisi e Sebastiano Battiato. "Organizing egocentric videos of daily living activities". Pattern Recognition 72 (dicembre 2017): 207–18. http://dx.doi.org/10.1016/j.patcog.2017.07.010.

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Refonaa, J., Bandaru Suhas, B. V. S. Bhaskar, S. L. JanyShabu, S. Dhamodaran, Sardar Maran, Maria Anu e M. Lakshmi. "Fall Detection and Daily Living Activity Recognition Logic Regression". Journal of Computational and Theoretical Nanoscience 17, n. 8 (1 agosto 2020): 3520–25. http://dx.doi.org/10.1166/jctn.2020.9223.

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It is a must to bring the fall detection system in to use with the increasing number of elder people in the world, because the most of them tend live voluntarily and at risk of injuries. Falls are dangerous in a few cases and could even lead to deadly injuries. A very robust fall detection system must be built in order to counter this problem. Here, we establish fall detection and recognition of daily live behavior through machine learning system. In order to detect different types of activities, including the detection of falls and day to-day activities, We use 2 shared archives for the accelerating and lateral speed data during this development. Logistic regression is used to determine motions such as drop, walk, climb, sit, stand and lie bases on the accelerating data and data on angular velocities. More specifically, the triaxial acceleration average value is used to achieve fall detection accuracy.

Nguyen, Thi-Hoa-Cuc, Jean-Christophe Nebel e Francisco Florez-Revuelta. "Recognition of Activities of Daily Living with Egocentric Vision: A Review". Sensors 16, n. 1 (7 gennaio 2016): 72. http://dx.doi.org/10.3390/s16010072.

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Salguero, Alberto, Macarena Espinilla, Pablo Delatorre e Javier Medina. "Using Ontologies for the Online Recognition of Activities of Daily Living". Sensors 18, n. 4 (14 aprile 2018): 1202. http://dx.doi.org/10.3390/s18041202.

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Avgerinakis, Konstantinos, Alexia Briassouli e Ioannis Kompatsiaris. "Activities of daily living recognition using optimal trajectories from motion boundaries". Journal of Ambient Intelligence and Smart Environments 7, n. 6 (20 novembre 2015): 817–34. http://dx.doi.org/10.3233/ais-150347.

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Cheng, Bo-Chao, Yi-An Tsai, Guo-Tan Liao e Eui-Seok Byeon. "HMM machine learning and inference for Activities of Daily Living recognition". Journal of Supercomputing 54, n. 1 (9 ottobre 2009): 29–42. http://dx.doi.org/10.1007/s11227-009-0335-0.

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Al Huda, Fais, Herman Tolle e Rosa Andrie Asmara. "Realtime Online Daily Living Activity Recognition Using Head-Mounted Display". International Journal of Interactive Mobile Technologies (iJIM) 11, n. 3 (27 aprile 2017): 67. http://dx.doi.org/10.3991/ijim.v11i3.6469.

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Human activity recognition is one of the popular research fields. The results of this study can be applied to many other fields such as the military, commercialism, and health. With the advent of the wearable head mounted display device mainly like google glass raises the possibility of this research. In this study tries to identify everyday activities are often called the ambient activity. Development of the system is done online using a smartphone and a head mounted display. The system produces an accuracy above 90%, which can be concluded that the system was able to recognize the activities with great accuracy.

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Tesi sul tema "Activities of daily living recognition":

Tayyub, Jawad. "Hierarchical modelling and recognition of activities of daily living". Thesis, University of Leeds, 2018. http://etheses.whiterose.ac.uk/22186/.

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Activity recognition is becoming an increasingly important task in artificial intelligence. Successful activity recognition systems must be able to model and recognise activities ranging from simple short activities spanning a few seconds to complex longer activities spanning minutes or hours. We define activities as a set of qualitatively interesting interactions between people, objects and the environment. Accurate activity recognition is a desirable task in many scenarios such as surveillance, smart environments, robotic vision etc. In the domain of robotic vision specifically, there is now an increasing interest in autonomous robots that are able to operate without human intervention for long periods of time. The goal of this research is to build activity recognition approaches for such systems that are able to model and recognise simple short activities as well as complex longer activities arising from long-term autonomous operation of intelligent systems. The research makes the following key contributions: 1. We present a qualitative and quantitative representation to model simple activities as observed by autonomous systems. 2. We present a hierarchical framework to efficiently model complex activities that comprise of many sub-activities at varying levels of granularity. Simple activities are modelled using a discriminative model where a combined feature space, consisting of qualitative and quantitative spatio-temporal features, is generated in order to encode various aspects of the activity. Qualitative features are computed using qualitative spatio-temporal relations between human subjects and objects in order to abstractly represent the simple activity. Unlike current state-of-the-art approaches, our approach uses significantly fewer assumptions and does not require any knowledge about object types, their affordances, or the constituent activities of an activity. The optimal and most discriminating features are then extracted, using an entropy-based feature selection process, to best represent the training data. A novel approach for building models of complex long-term activities is presented as well. The proposed approach builds a hierarchical activity model from mark-up of activities acquired from multiple annotators in a video corpus. Multiple human annotators identify activities at different levels of conceptual granularity. Our method automatically infers a ‘part-of’ hierarchical activity model from this data using semantic similarity of textual annotations and temporal consistency. We then consolidate hierarchical structures learned from different training videos into a generalised hierarchical model represented as an extended grammar describing the over all activity. We then describe an inference mechanism to interpret new instances of activities. Simple short activity classes are first recognised using our previously learned generalised model. Given a test video, simple activities are detected as a stream of temporally complex low-level actions. We then use the learned extended grammar to infer the higher-level activities as a hierarchy over the low-level action input stream. We make use of three publicly available datasets to validate our two approaches of modelling simple to complex activities. These datasets have been annotated by multiple annotators through crowd-sourcing and in-house annotations. They consist of daily activity videos such as ‘cleaning microwave’, ‘having lunch in a restaurant’, ‘working in an office’ etc. The activities in these datasets have all been marked up at multiple levels of abstraction by multiple annotators, however no information on the ‘part-of’ relationship between activities is provided. The complexity of the videos and their annotations allows us to demonstrate the effectiveness of the proposed methods.

Viard, Kévin. "Modelling and Recognition of Human Activities of Daily Living in a Smart Home". Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLN022/document.

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La plupart des travaux réalisés dans le domaine de l'assistance à l'autonomie à domicile (AAL) reposent sur l'utilisation de capteurs visuels et audio tels que des caméras. Or, ces capteurs sont souvent rejetés par le patient à cause de leur caractère invasif. Des approches alternatives requièrent l'utilisation de capteurs embarqués sur la personne (GPS, bracelets électroniques ou puces RFID dans les vêtements...), et leur pertinence est donc ramenée à l'hypothèse que les personnes les portent effectivement, sans jamais les rejeter ni les oublier. Pour ces raisons, dans cette thèse, nous trouvons plus pertinentes les approches uniquement basées sur l'utilisation de capteurs binaires intégrés dans l'habitat, tels que les détecteurs de mouvements, les tapis sensitifs ou les barrières optiques. Dans un tel contexte technologique, il devient intéressant d'utiliser les paradigmes, les modèles et les outils des systèmes à événement Discrets (SED), initialement plutôt développés pour la modélisation, l'analyse et la commande des systèmes industriels complexes. Dans ces travaux de thèse, l'objectif est de construire une approche pour la modélisation et le suivi des habitudes de vie, basée sur les modèles et les paradigmes des SED et répondant à une problématique qui s'énonce de la manière suivante : L'objectif est de développer un cadre global pour découvrir et reconnaître les activités de la vie quotidienne d'un habitant vivant seul dans une maison intelligente. Cette maison intelligente doit être équipée uniquement de capteurs binaires, l'étiquetage par des experts des activités observées ne doit pas être nécessaire et les activités peuvent être représentées par des modèles probabilistes. La première méthode présentée dans cette thèse permet, à partir d'une base de données d'apprentissage et d'une description experte des activités à modéliser listées par des médecins, de construire pour chaque activité un modèle sous la forme d'un automate à état-fini probabiliste (PFA). La seconde méthode développée lors de cette thèse permet d'estimer en temps réel, à partir des seules données observées par les capteurs ambiants, quelle activité la personne observée réalise effectivement. Les méthodes décrites dans cette thèse sont illustrées en utilisant les données générées localement via l'utilisation d'un appartement prêté par ENS Paris-Saclay équipé pour répondre aux besoins expérimentaux de cette thèse
Most of the work done in the field of ambient assisted living (AAL) is based on the use of visual and audio sensors such as cameras. However, these sensors are often rejected by the patient because of their invasiveness. Alternative approaches require the use of sensors embedded on the person (GPS, electronic wristbands or RFID chips in clothing ...), and their relevance is therefore reduced to the assumption that people actually wear them, without rejecting nor forgetting them. For these reasons, in this thesis, we find more relevant the approaches based on the use of binary sensors integrated into the habitat only, such as motion detectors, sensory mats or optical barriers. In such a technological context, it becomes interesting to use paradigms, models and tools of Discrete Event Systems (DES), initially developed for modeling, analysis and control of complex industrial systems. In this thesis work, the goal is to build an activity of daily living modeling and monitoring approach, based on the models and the paradigm of the DES and answering a problem that is expressed as follows:The objective is to develop a global framework to discover and recognise activities of daily living of an inhabitant living alone in a smart home. This smart home have to be equipped with binary sensors only, expert labeling of activities should not be needed and activities can be represented by probabilistic models. The first method presented in this thesis allows to build a probabilistic finite-state automata (PFA) from a learning database and an expert description of the activities to be modeled given by the medical staff. The second method developed during this thesis estimates, according to the observations, the activity performed by the monitored inhabitant. The methods described in this thesis are applied on data generated using an apartment lent by ENS Paris-Saclay and equipped according the experimental needs of this thesis
La maggior parte dei lavori nel settore dell’Ambient Assisted Living (AAL) si basasull’uso di sensori visivi e audio come le telecamere. Tuttavia, questi sensori sonospesso rifiutati dal paziente a causa della loro natura invasiva. Gli approcci alternativi richiedono l’uso di sensori integrati nella persona (GPS, bracciali elettronici o chipRFID...), e la loro rilevanza è quindi ridotta all’ipotesi che le persone li indossino effettivamente, senza mai rifiutarli o dimenticarli.Per questi motivi, in questa tesi, troviamo approcci più rilevanti basati esclusivamente sull’uso di sensori binari integrati nell’habitat, come rilevatori di movimento,tappeti sensoriali o barriere fotoelettriche.In tale contesto tecnologico, diventa interessante utilizzare i paradigmi, i modelli egli strumenti dei sistemi ad eventi discreti (SED), inizialmente sviluppati per la modellazione, l’analisi e il controllo di sistemi industriali complessi.In questo lavoro di tesi, l’obiettivo è quello di presentare un metodo per la modellazione e il monitoraggio delle abitudini di vita, basato sui modelli e paradigmi di SEDe rispondendo ad un problema che si esprime come segue : L’obiettivo è quello di sviluppare un quadro globale per rivelare e riconoscere le attività della vita quotidiana di una persona che abita da sola in una smart home chedovrebbe essere dotata solo di sensori binari. Inoltre si suppone che non sia necessarial’etichettatura delle attività osservate da parte di un esperto e tali attività sono rappresentate da modelli probabilistici.Il primo metodo presentato in questa tesi permette di costruire un modello probabilistico di automa a stati finiti (PFA) ottenuto da un database di apprendimento e unadescrizione delle attività da parte di medici. Il secondo metodo sviluppato in questa tesi stima, alla luce delle osservazioni, qualeattività svolge la persona osservata. I metodi descritti sono illustrati utilizzando dati generati localmente attraverso l’usodi un appartamento messo a disposizione da ENS Paris-Saclay e attrezzato per soddisfarele esigenze sperimentali di questa tesi

Li, Yunjie. "Applying Data Mining Techniques on Continuous Sensed Data : For daily living activity recognition". Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-23424.

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Nowadays, with the rapid development of the Internet of Things, the applicationfield of wearable sensors has been continuously expanded and extended, especiallyin the areas of remote electronic medical treatment, smart homes ect. Human dailyactivities recognition based on the sensing data is one of the challenges. With avariety of data mining techniques, the activities can be automatically recognized. Butdue to the diversity and the complexity of the sensor data, not every kind of datamining technique can performed very easily, until after a systematic analysis andimprovement. In this thesis, several data mining techniques were involved in theanalysis of a continuous sensing dataset in order to achieve the objective of humandaily activities recognition. This work studied several data mining techniques andfocuses on three of them; Decision Tree, Naive Bayes and neural network, analyzedand compared these techniques according to the classification results. The paper alsoproposed some improvements to the data mining techniques according to thespecific dataset. The comparison of the three classification results showed that eachclassifier has its own limitations and advantages. The proposed idea of combing theDecision Tree model with the neural network model significantly increased theclassification accuracy in this experiment.

Peng, Yingli. "Improvement of Data Mining Methods on Falling Detection and Daily Activities Recognition". Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-25521.

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With the growing phenomenon of an aging population, an increasing numberof older people are living alone for domestic and social reasons. Based on thisfact, falling accidents become one of the most important factors in threateningthe lives of the elderly. Therefore, it is necessary to set up an application to de-tect the daily activities of the elderly. However, falling detection is difficult to recognize because the "falling" motion is an instantaneous motion and easy to confuse with others.In this thesis, three data mining methods were employed on wearable sensors' value; first which contains the continuous data set concerning eleven activities of daily living, and then an analysis of the different results was performed. Not only could the fall be detected, but other activities could also be classified. In detail, three methods including Back Propagation Neural Network, Support Vector Machine and Hidden Markov Model are applied separately to train the data set.What highlights the project is that a new idea is put forward, the aim of which is to design a methodology of accurate classification in the time-series data set. The proposed approach, which includes obtaining of classifier parts and the application parts allows the generalization of classification. The preliminary results indicate that the new method achieves the high accuracy of classification,and significantly performs better than other data mining methods in this experiment.

Ball, Stephen. "Investigating telemonitoring technologies for the detection of activities and the application of BLE in smart homes for elderly independent living". Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/123510/1/Stephen%20Ball%20Thesis.pdf.

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Due to the rise in the elderly population and the prevalence of chronic diseases, healthcare organizations around the world are faced with an economic burden which will continue to grow. For this reason there is an urgent demand to reduce the intake of elders in hospitals and nursing homes by allowing them to live independently for greater lengths of time. In response to this demand, researchers are strongly focusing on 'telemonitoring', which is the use of information technology (IT) to monitor the health status of an individual from a remote location (e.g. their home). The first aim of this thesis was to investigate how telemonitoring technologies can detect elderly activities for health assessment purposes. To assess a patient's health status holistically, a wide variety of factors needed be considered by practitioners. Currently many telemonitoring technologies in research have addressed these factors/assessments by monitoring elderly activities. However based on the literature reviews, researchers have not been able to develop a comprehensive understanding of how these technologies support each assessment. Therefore the first contribution in chapter 3 of this thesis addresses this gap. A literature review was conducted where 215 telemonitoring technologies were identified from 82 papers, published between 2000 and 2016. Six assessments which involve monitoring of activities were identified as (1) mobility, (2) nutrition, (3) safety, (4) cognitive, (5) social, and (6) routine. All included technologies were categorized into six tables according to the assessment that they supported. From assessing the contents of these tables, it was found that a significant portion of ITs relate to mobility, nutritional, safety and routine assessments. Many of the studies were found to assess technologies inside of laboratory setting and still require improvement before they are suited for real world application. It also found that many of the technologies were not equipped with wireless communication. In recent years recently have been focusing been integrating wireless sensing technology into telemonitoring applications. Many of these wireless technologies are small, unobtrusive, and usually need to be powered by small batteries (e.g. coin cell) which have limited capacity. For this reason, researchers have had difficulties prolonging battery life to a duration that is practical. However the recent release of Bluetooth Low Energy (BLE) has the potential of resolving this issue due to its power saving qualities. The 2nd aim of this thesis is to assess the performance of Bluetooth Low Energy (BLE) in telemonitoring frameworks using advertising mode. Advertising mode is often used for device discovery purposes, however it can also be used to send context data without the need for device connection establishment. This method has received little investigation from researchers and yet it has the potential of offering advantages such as reduction in power consumption and manufacturing costs. Therefore in this thesis, the performance of BLE advertising mode was used within two telemonitoring applications. Firstly, a new device called 'BLUESOUND' is proposed. The device uses ultrasound sensing technology which can efficiently differentiate multiple residents in a home environment based on their height. The device consists of three sensing/communication modules: A Passive Infrared (PIR) occupancy module, an ultrasound array module and a BLE communication module. The PIR occupancy module is used to detect walking direction, while the ultrasound array measures the resident's height. The combination of these two technologies can also be used to detect a resident's velocity. BLE advertising mode is used to communicate acquired data to a smart phone gateway/database. A new embedded algorithm was able to increase the energy efficiency of the identification technology. Comprehensive modelling and experimentation was undertaken to assess the performance the BLUESOUND device. The BLUESOUND device was able to distinguish between multiple resident identities by measuring height accurately. Currently researchers have developed various wearable ECG monitors as there is a demand to detect the onset of cardiac disease earlier in the elderly population. However most of these devices have only lasted a couple of days on a coin cell battery which is not practical. Therefore the performance of BLE advertising mode was explored using a virtual BLE based ECG model in MATLAB. To further minimize power consumption, an ECG extraction technique (based on the 'So and Chan' algorithm [1]) was used in the model to extract some of the most significant points on the signal. Based on three simulation trails, ECG data was transferred to a scanning device with high accuracy (average of 99.62%). It was estimated that the virtual system is approximately 13 times more energy efficient compared to sending ECG stream data continuously when a connection is established.

Zaineb, Liouane. "Services e-santé basés sur la reconnaissance et la prédiction des activités quotidiennes dans les espaces intelligents". Thesis, Rennes 1, 2018. http://www.theses.fr/2018REN1S109.

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Les progrès de la technologie des capteurs et leur disponibilité ont permis de mesurer diverses propriétés et activités des habitants dans une maison intelligente. Cependant, l’obtention de connaissances significatives à partir d’une grande quantité d’informations collectées à partir d’un réseau de capteurs n’est pas une tâche simple. En raison de la complexité du comportement des habitants, l’extraction d’informations significatives et la prédiction précise des valeurs représentant les activités futures d’un occupant sont des défis de recherche [6]. L’objectif principal de notre travail de thèse est d’assurer une analyse efficace des données recueillies à partir des capteurs d’occupation dans une maison intelligente. A ce propos, ce travail se base sur la reconnaissance et l’évaluation des activités quotidiennes d’une personne âgée dans le but d’observer, de prédire et de suivre l’évolution de son état de dépendance, de santé et de détecter par la même occasion, la présence d’une perte ou d’une perturbation de l’autonomie en temps réel
Advances in sensor technology and their availability have measured various properties and activities of residents in a smart home. However, obtaining significant knowledge from a large amount of information collected from a sensor network is not a simple task. Due to the complexity of the behavior of the inhabitants, the extraction of meaningful information and the accurate prediction of values representing the future activities of an occupant are research challenges. The main objective of our thesis work is to ensure an efficient analysis of data collected from occupancy sensors in a smart home. In this regard, this work is based on the recognition and evaluation of the daily activities of an elderly person in order to observe, predict and monitor the evolution of his state of dependence, health and to detect by the same occasion, the presence of a loss or a disruption of autonomy in real time

El, Khadiri Yassine. "Inférence bayésienne pour la détection des activités de la vie quotidienne pour faciliter le maintien à domicile des personnes âgées". Electronic Thesis or Diss., Université de Lorraine, 2021. http://www.theses.fr/2021LORR0251.

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L'augmentation de la population séniore se révèle être un enjeu de taille et une grande question de santé publique. La part démographique des personnes âgées s'agrandit de plus en plus grâce au progrès et avancés de la médecine et nos systèmes de santé. Néanmoins le vieillissement de cette population implique naturellement une pléthore de problèmes de dépendance qui y sont associés, ceci bien sûr exponentiellement. Les maisons de retraite sont des solutions généralement coûteuses et très peu appréciées. En conséquence, des solutions plus adaptées basées sur l'aide au maintien à domicile ce développement de plus en plus ces dernières années. Cette problématique se retrouve dans la croisée des chemins entre les technologies de capteurs, la télétransmission de données, l'assistance aux personnes âgées à mobilité réduite et le suivi d'activités. Cette thèse explore l'application d'algorithmes d'analyse de données pour le suivi d'activités des personnes âgées à domicile. L'idée étant qu'un suivi régulier des résidents permet d'inférer leur état de dépendance ou d'autonomie et permet aux personnels soignants d'intervenir en cas de détection d'un début de dégradation. Nous avons exploré et adapté certaines méthodes d'inférence bayésienne et segmentation de séries temporelles pour la reconnaissance d'activités. Et ensuite, nous avons proposé un outil de visualisation permettant de faciliter la détection d'anomalies ou changements de rythme de vie. Ce travail s'inscrit dans le cadre d'une thèse CIFRE. Ainsi tous les méthodes et algorithmes explorés ont été mis en production et sont exploités par la solution d'aide à domicile commercialisé par la société Diatelic
The increase of the senior population constitutes a major public health issue. The demographic share of the elderly is ever more growing thanks to the progress and advances in medicine and our health care systems. However, with the aging of this population comes a plethora of dependency problems, and this, of course, exponentially.Retirement homes are an expensive and not very popular solution. As a result, we are seeing a surge in home assisted living solutions in the recent years.This topic is in the crossroads between sensor technologies, data transmission, assistance to elderly people and activity monitoring.This thesis explores the application of data analysis algorithms for activity monitoring of elderly people at home. The idea is that with day-to-day monitoring of residents it is possible to infer their autonomy and capacity to perform day-to-day tasks. It also allows caregivers to intervene in cases where the start of some degradation is detected.We explored and adapted some Bayesian inference and time series segmentation methods for activity recognition. And then, we proposed a visualization tool to facilitate the detection of anomalies or changes in everyday habits.This work is part of a CIFRE thesis. The methods and algorithms presented have been put into production and are packaged into Diatelic's the assisted living commercial solution

Burgio, Francesca. "Numerical Activities of Daily Living (NADL) and Numerical Activities of Daily Living - Financial (NADL-F) in Neurological Diseases". Doctoral thesis, Università degli studi di Padova, 2016. http://hdl.handle.net/11577/3422287.

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What is the impact of acalculia upon an individual’s everyday life? In clinical practice, a few measures of Activities of Daily Living are available. In these batteries, however, numerical abilities were not distinguished from other abilities. As a consequence, no instrument has been made available so far to measure the nature and the extent of damage to everyday life specifically brought by acalculia in a given individual. The first aim of this series of studies was to build and validate an instrument, the Numerical Activities of Daily Living (NADL), designed to measure this impact. The first section of the thesis describes the psychometric properties of the newly created NADL and the specific profiles observed among patients suffering of several neurological diseases (a specific study was devoted to neurofibromatosis type 1) by using this instrument; patients with a right hemisphere focal lesion were also the object of a specific study). A further development of NADL (NADL-Children) was built for the assessment of numerical activities of daily living in children: it helped to predict math school performance after the first year of primary school. In the second section we deepened one particular aspect of daily living activities requiring numbers (i.e. dealing with finances) found to be critical in our studies employing NADL. Indeed, the loss of financial capacity can have serious legal, economical, and personal consequences on an individual. Therefore, we additionally created a tool (Numerical Activities of Daily Living - Financial; NADL-F) that was also successfully validated in clinical populations in Italy as the second scope of this thesis. We also explored the differences in financial and numerical domains between MCI and healthy controls by means of NADL and NADL-F. The cognitive domains found to be involved in the deficit may be appropriate targets for future intervention studies aimed at preserving functional independence in individuals with MCI. Finally we also correlated the performance in the NADL and NADL-F test with anatomical brain changes. The investigation of the neural correlates of financial and other daily numerical abilities will help us to better define the knowledge of this high-level functions; moreover the neuroimaging studies will shed light on the brain areas related to the performance in financial tasks, and will be useful to find out the predictors of the time-course of decline in financial capacities.
Qual'è l'impatto dell'acalculia sulla vita quotidiana? Nella pratica clinica, solo pochi strumenti sono disponibili. In queste batterie, oltretutto, le abilità numeriche non vengono distinte dalle altre abilità della vita quotidiana. Di conseguenza non vi è alcuno strumento che possa misurare l'impatto della acalculia nella vita quotidiana. Il primo obiettivo di questa serie di studi è stato dunque quello di costruire e validare uno strumento, il Numerical Activities of Daily Living (NADL), per misurare questo impatto. La prima sezione della tesi descrive le proprietà psicometriche del test NADL ed in particolar modo, vengono esplorati diversi profili di errori specifici per ogni singola patologia neurologica considerata ad esempio nei pazienti con neurofibromatosi e nei pazienti con lesione emisferica destra. Un ulteriore sviluppo del NADL (NADL-Children) è stato costruito al fine di valutare le abilità numeriche della vita quotidiana nei bambini. Nella seconda sezione viene approfondito un particolare aspetto delle attività di vita quotidiana in cui l'uso dei numeri è essenziale, l'uso del denaro. La perdita della capacità finanziaria può avere delle serie implicazioni sul piano legale ed economico oltre che personale. Abbiamo dunque creato uno strumento specificatamente pensato per questo fine (Numerical Activities of Daily Living - Financial; NADL-F). Il secondo obiettivo della tesi è stato quello di validare lo strumento per poterlo rendere diponibile in Italia e applicarlo a differenti popolazioni cliniche. Abbiamo inoltre esplorato le differenze nei domini numerici e finanziari sia in soggetti di controllo sani che in pazienti con deterioramento cognitivo lieve utilizzando sia il NADL che il NADL-F. I domini cognitivi che sono risultati essere implicati nel deficit potrebbero essere l'obiettivo di futuri interventi riabilitativi di studi successivi che hanno come obiettivo quello di preservare l'indipendenza funzionale e l'autonomia dei pazienti con deterioramento cognitivo lieve. Infine, abbiamo correlato la performance sia al NADL che al NADL-F con le differenze volumetriche cerebrali associate sia nei pazienti che nei controlli. Lo studio dei correlati neurali delle abilità numeriche e finanziarie ci aiuterà a fare maggiore chiarezza nello studio di queste funzioni di alto livello. Inoltre gli studi di neuroimmagine potranno chiarire le aree cerebrali legate alla performance in questi compiti che saranno utili per trovare dei predittori del declino nel corso del tempo di queste capacità.

Jackson, Lauren Innes. "Depression, Activities of Daily Living, and Retirement". Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5220/.

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Depression is a common clinical and subclinical psychiatric disorder in the middle-age to older adult population. This study examined the relationship between depression and activities of daily living (ADLs) in middle-age to older adults. This study examined longitudinal data from the 1998, wave 4, and 2000, wave 5, of the Health and Retirement Study (HRS), a National Panel Study sponsored by the National Institute on Aging. A negative cross-sectional and longitudinal relationship between higher ADL scores and depression was hypothesized. A goal of the present study was to determine the temporal precedence of these two constructs using a cross-lag panel design to first examine the cross-sectional relationship between ADLs and depression at time-one and at time-two, and then the time-one to time-two longitudinal relationships to examine temporal precedence possible causal relationships. Finally, differences in these correlational relationships by retirement status and then by marital status were tested. There were several interesting findings, including those who were retired in both 1998 and 2000 reported fewer ADLs (i.e., worse functioning), but also reported better health than those who were working in both 1998 and 2000. Similarly, those people who were not married in both 1998 and 2000 reported fewer ADLs but better health than those who were married in both 1998 and 2000. Married individuals reported fewer depressive symptoms than those who were not married.

Cheng, Pei Lai. "Biomechanical study of upper limb activities of daily living". Thesis, University of Strathclyde, 1996. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=20389.

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The kinematic and kinetic characteristics of arm movement during four activities of daily living: lifting a weight, driving a steering wheel, opening/closing a door and cutting were investigated in this study by using a human movement analysis system comprising a 6 camera Vicon motion analysis system, a 6 component strain-gauged transducer, a specially designed and instrumented steering wheel simulation system, a door and a cutting plate. The most important achievements of this study are: (1) Implementation of the residual analysis technique into a computer program to filter the noisy kinematic data at an autoselected cut-off frequency for each data sequence. (2) The development of a new method of representing the velocity and acceleration of points of interest using the phase plane presentation. It was found that driving is the most complicated activity investigated in this study according to the range of arm movement. From the kinetic results, it was found that the order of difficulty of the four activities can be arranged as cutting, door opening/closing, lifting, and driving according to the magnitude of the maximum resultant total shoulder moment. The difficulty of the lifting activity increased with the weight to be lifted and the height of lifting. It was also found that the major component of the shoulder moment is the flexion/extension moment for most of the activities except driving, therefore it is concluded that having sufficient shoulder flexion/extension strength is most important for conducting most upper limb activities of daily living. In addition, the results of this study provide information for improving the understanding of the biomechanics of the upper limb activities and for clinical reference.

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Libri sul tema "Activities of daily living recognition":

Pecchia, Leandro, Liming Luke Chen, Chris Nugent e José Bravo, a cura di. Ambient Assisted Living and Daily Activities. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13105-4.

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Holland, Audrey L. CADL-2 communication activities of daily living: Examiner's manual. 2^a ed. Austin, Tex: pro-ed, 1999.

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Study Group on Transcultural Rehabilitation Medicine., a cura di. A guide to ADL: (the activities of daily living). Delft: Eburon, 1993.

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P, LaPlante Mitchell, Kaye H. Stephen, National Institute on Disability and Rehabilitation Research (U.S.) e Educational Resources Information Center (U.S.), a cura di. Need for assistance in the activities of daily living. [Washington, DC: U.S. Dept. of Education, National Institute on Disability and Rehabilitation Research], 1997.

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Cedar, S. H. Biology for health: Applying the activities of daily living. Houndsmills, Basingstoke: Palgrave Macmillan, 2012.

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Munro, Kate. Independent living. Edinburgh: Churchill Livingstone, 1992.

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Henriksson, Chris. Living with fibromyalgia: A study of the consequences for daily activities. Linko ping, Sweden: Dept. of Caring Sciences & Dept. of Rheumatology, Faculty of Health Sciences, Linko ping University, 1995.

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Kennedy, Jae. A Profile of adults needing assistance with activities of daily living, 1991-1992. Washington, D.C: U.S. Dept. of Education, Office of Special Education and Rehabilitative Services, 1997.

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Kennedy, Jae. A profile of adults needing assistance with activities of daily living, 1991-1992. [Washington, D.C.]: U.S. Dept. of Education, Office of Special Education and Rehabilitative Services, National Institute on Disability and Rehabilitation Research, 1997.

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Árnadóttir, Guðrún. The brain and behavior: Assessing cortical dysfunction through activities of daily living (ADL). St. Louis: Mosby, 1990.

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Capitoli di libri sul tema "Activities of daily living recognition":

Alam, Md Jahangir, Yazid Attabi, Patrick Kenny, Pierre Dumouchel e Douglas O’Shaughnessy. "Automatic Emotion Recognition from Cochlear Implant-Like Spectrally Reduced Speech". In Ambient Assisted Living and Daily Activities, 332–40. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13105-4_48.

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Cartas, Alejandro, Juan Marín, Petia Radeva e Mariella Dimiccoli. "Recognizing Activities of Daily Living from Egocentric Images". In Pattern Recognition and Image Analysis, 87–95. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58838-4_10.

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Arias Tapia, Susana A., Sylvie Ratté, Héctor F. Gómez A., Alexandra González Eras, José Barbosa, Juan Carlos Torres, Ruth Reátegui Rojas et al. "First Contribution to Complex Emotion Recognition in Patients with Alzheimer’s Disease". In Ambient Assisted Living and Daily Activities, 341–47. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13105-4_49.

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Synnott, Jonathan, Chris Nugent e Paul Jeffers. "A Thermal Data Simulation Tool for the Testing of Novel Approaches to Activity Recognition". In Ambient Assisted Living and Daily Activities, 10–13. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13105-4_2.

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Siddiqi, Muhammad Hameed, Rahman Ali, Byeong Ho Kang e Sungyoung Lee. "A New Feature Extraction Technique for Human Facial Expression Recognition Systems Using Depth Camera". In Ambient Assisted Living and Daily Activities, 131–38. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13105-4_21.

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Lozano-Monasor, Elena, María T. López, Antonio Fernández-Caballero e Francisco Vigo-Bustos. "Facial Expression Recognition from Webcam Based on Active Shape Models and Support Vector Machines". In Ambient Assisted Living and Daily Activities, 147–54. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13105-4_23.

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Gu, Feng, Francisco Flórez-Revuelta, Dorothy Monekosso e Paolo Remagnino. "A Multiple Kernel Learning Based Fusion Framework for Real-Time Multi-View Action Recognition". In Ambient Assisted Living and Daily Activities, 26–33. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13105-4_5.

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Liouane, Zaineb, Tayeb Lemlouma, Philippe Roose, Fréderic Weis e Hassani Messaoud. "An Improved Elman Neural Network for Daily Living Activities Recognition". In Advances in Intelligent Systems and Computing, 697–707. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53480-0_69.

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Banos, Oresti, Miguel Damas, Hector Pomares e Ignacio Rojas. "Automatic Recognition of Daily Living Activities Based on a Hierarchical Classifier". In Advances in Computational Intelligence, 185–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21498-1_24.

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Pires, Ivan Miguel, Gonçalo Marques, Nuno M. Garcia, Francisco Flórez-Revuelta, Maria Canavarro Teixeira, Eftim Zdravevski e Susanna Spinsante. "Recognition of Activities of Daily Living Based on a Mobile Data Source Framework". In Bio-inspired Neurocomputing, 321–35. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5495-7_18.

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Atti di convegni sul tema "Activities of daily living recognition":

Avgerinakis, K., A. Briassouli e I. Kompatsiaris. "Recognition of Activities of Daily Living". In 2012 IEEE 24th International Conference on Tools with Artificial Intelligence (ICTAI 2012). IEEE, 2012. http://dx.doi.org/10.1109/ictai.2012.181.

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Bergeron, Frederic, Sylvain Giroux, Kevin Bouchard e Sebastien Gaboury. "RFID based activities of daily living recognition". In 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE, 2017. http://dx.doi.org/10.1109/uic-atc.2017.8397548.

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Poularakis, Stergios, Konstantinos Avgerinakis, Alexia Briassouli e Ioannis Kompatsiaris. "Computationally efficient recognition of activities of daily living". In 2015 IEEE International Conference on Image Processing (ICIP). IEEE, 2015. http://dx.doi.org/10.1109/icip.2015.7350797.

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Bergeron, Frédéric, Kevin Bouchard, Sylvain Giroux, Sébastien Gaboury e Bruno Bouchard. "Real-Time Constraints for Activities of Daily Living Recognition". In PETRA '16: 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2910674.2935840.

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Liouane, Zaineb, Tayeb Lemlouma, Philippe Roose, Fréderic Weis e Hassani Messaoud. "A Markovian-based Approach for Daily Living Activities Recognition". In 5th International Conference on Sensor Networks. SCITEPRESS - Science and and Technology Publications, 2016. http://dx.doi.org/10.5220/0005809502140219.

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Negrete Ramírez, José Manuel, e Yudith Cardinale. "Activities of Daily Living Detection on Healthcare: A Categorization". In iWOAR '22: 7th international Workshop on Sensor-based Activity Recognition and Artificial Intelligence. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3558884.3558887.

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Masciadri, Andrea, Sara Comai e Fabio Salice. "SMARE: Semi-supervised Method for Activities of daily living REcognition". In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 2019. http://dx.doi.org/10.1109/smc.2019.8914279.

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Das, Srijan, Monique Thonnat e Francois Bremond. "Looking deeper into Time for Activities of Daily Living Recognition". In 2020 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2020. http://dx.doi.org/10.1109/wacv45572.2020.9093575.

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Chinpanthana, Nutchanun, e Yunyu Liu. "Human Activities of Daily Living Recognition with Graph Convolutional Network". In ICCAI '20: 2020 6th International Conference on Computing and Artificial Intelligence. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3404555.3404557.

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Li, Jiawei, Shu-Tao Xia e Qianggang Ding. "Multi-level Recognition on Falls from Activities of Daily Living". In ICMR '20: International Conference on Multimedia Retrieval. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3372278.3390702.

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Rapporti di organizzazioni sul tema "Activities of daily living recognition":

Bu, Qingguo, Wenqi Yu, Hongzhen Lian, Lei Zhang, Dandan Wang e Xueping Wu. Effect of Exercise Intervention on the Activities of Daily Living of the Elderly: A Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, aprile 2021. http://dx.doi.org/10.37766/inplasy2021.4.0136.

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Flores-Bello, Cristina, Elsa Correa-Muñoz, Martha Asunción Sánchez-Rodríguez e Víctor Manuel Mendoza-Núñez. Effect of self-care programs on functional capacity and wellbeing in community-dwelling older adults. A systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, maggio 2023. http://dx.doi.org/10.37766/inplasy2023.5.0053.

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Review question / Objective: The aim of this systematic review is to present a synthesis of knowledge about the effect of self-care programs on the functional capacity in community-dwelling older adults. For this reason, the following question will be addressed: ¿What is the effect of self-care programs on the functional capacity in community-dwelling older adults? P: Community-dwelling older adults; I: Self-care programs for healthy aging; C: Without self-care programs; O: Functional capacity (SPPB, Short Physical Performance Battery; IADL, instrumental activities of daily living; AADL, advanced activities of daily living) and wellbeing (self-esteem, quality of life, life satisfaction). Information sources: A systematic search was performed of scientific data on five data bases: PubMed, Web of Science, Scopus, SciELO, LILACS, and TESIUNAM.

Inoue, Nozomu. Prediction of Pathologic Fracture Risk in Activities of Daily Living and Rehabilitation of Patients with Metastatic Breast Carcinoma of the Pelvis and Femur. Fort Belvoir, VA: Defense Technical Information Center, agosto 2001. http://dx.doi.org/10.21236/ada398168.

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Inoue, Nozomu. Prediction of Pathologic Fracture Risk in Activities of Daily Living and Rehabilitation of Patients With Metastatic Breast Carcinoma of the Pelvis and Femur. Fort Belvoir, VA: Defense Technical Information Center, agosto 2002. http://dx.doi.org/10.21236/ada408690.

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Jiang, Jieting, Xinyu Li, Wang Hui, Huang Lan e Caiqin Wu. The effect of computerized cognitive training on improving the cognitive impairment and the activities of daily living in patients with post-stroke cognitive impairment. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, marzo 2021. http://dx.doi.org/10.37766/inplasy2021.3.0059.

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Zhuo, Yue, e Hong Zhang. Different Acupuncture Intervention Time-points for Improving Capacity in Motor Function and Activities of Daily Living after Stroke: A Systematic Review and Network Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, dicembre 2020. http://dx.doi.org/10.37766/inplasy2020.12.0060.

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WU, Jingyi, Jiaqi LI, Ananda Sidarta e Patrick Wai Hang Kwong. Neural mechanisms of bimanual coordination in humans and application of neuromodulation therapy: a scoping review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, maggio 2023. http://dx.doi.org/10.37766/inplasy2023.5.0080.

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Background: Bimanual coordination deficits are one of the most common characteristics of people with stroke, which have an adverse influence on their independence of activities daily living and other occupational activities. Existing studies and reviews mainly focused on how to improve motor impairment of the affected limb and cortical activation and functional connectivity in the impaired brain hemisphere by a series of rehabilitation strategies, e.g., non-invasive brain stimulation and rehabilitation robotics. It should be noted that functional bilateral abilities are not a simple compound and a combination of one-handed skills. Therefore, the bimanual coordination dysfunctions still need to be explored and addressed in clinical practice. Better understandings of the neural mechanisms underlying bilateral cooperative tasks in healthy subjects and changes in neural activities in stroke patients help foster the development of effective rehabilitation strategies, such as TMS and tDCS, and enhance the bimanual coordination through stimulating altered cortical areas, which is essential for boosting the independence and quality of daily life in stroke individuals.

Li, Ruo-wei, Yuan Xia, Yong-jie Li, Yue Lu e Sheng Hu. Efficacy evaluation of different stimulation types with transcranial direct current stimulation on upper limb motor function and activities of daily living in patients after stroke: A network Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, dicembre 2020. http://dx.doi.org/10.37766/inplasy2020.12.0021.

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Nguyen, Brenda, Ayesha Raza, Sara Abdullah, Antonia Giannarakos, Ian Zenlea e Cilia Mejia-Lancheros. The Role of Occupational Therapy in Improving Participation in Activities of Daily Living (Self-Care, Leisure, Productivity) for Adolescents Aged 10-19 with Type 1 Diabetes: A Scoping Review Protocol. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, aprile 2024. http://dx.doi.org/10.37766/inplasy2024.4.0011.

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