A multidisciplinary telemedicine approach for managing frailty in Parkinson's disease. A longitudinal, case-control study.

Introduction: The interaction between frailty and Parkinson's disease (PD) is still unknown. This study aimed to study the effectiveness of a multidisciplinary telemedicine program in reducing frailty in Parkinson's disease.

Methods: Longitudinal, randomized, case-control study.

Computer Vision for Parkinson's Disease Evaluation: A Survey on Finger Tapping.

Parkinson's disease (PD) is a progressive neurodegenerative disorder whose prevalence has steadily been rising over the years. Specialist neurologists across the world assess and diagnose patients with PD, although the diagnostic process is time-consuming and various symptoms take years to appear, which means that the diagnosis is prone to human error. The partial automatization of PD assessment and diagnosis through computational processes has therefore been considered for some time.

Semi-supervised learning for industrial fault detection and diagnosis: A systemic review.

The automation of Fault Detection and Diagnosis (FDD) is a central task for many industries today. A myriad of methods are in use, although the most recent leading contenders are data-driven approaches and especially Machine Learning (ML) methods. ML algorithms fall into two main categories: supervised and unsupervised methods, depending on whether or not the instances are labeled with the expected outputs.

Improvements for Therapeutic Intervention from the Use of Web Applications and Machine Learning Techniques in Different Affectations in Children Aged 0-6 Years.

Technological advances together with machine learning techniques give health science disciplines tools that can improve the accuracy of evaluation and diagnosis. The objectives of this study were: (1) to design a web application based on cloud technology (eEarlyCare-T) for creating personalized therapeutic intervention programs for children aged 0-6 years old; (2) to carry out a pilot study to test the usability of the eEarlyCare-T application in therapeutic intervention programs. We performed a pilot study with 23 children aged between 3 and 6 years old who presented a variety of developmental problems.

Adopting a multidisciplinary telemedicine intervention for fall prevention in Parkinson's disease. Protocol for a longitudinal, randomized clinical trial.

Background: Approximately 40-70% of people with Parkinson's disease (PD) fall each year, causing decreased activity levels and quality of life. Current fall-prevention strategies include the use of pharmacological and non-pharmacological therapies. To increase the accessibility of this vulnerable population, we developed a multidisciplinary telemedicine program using an Information and Communication Technology (ICT) platform.

Videoconferencing Software Options for Telemedicine: A Review for Movement Disorder Neurologists.

The use of telemedicine has increased to address the ongoing healthcare needs of patients with movement disorders. We aimed to describe the technical and basic security features of the most popular telemedicine videoconferencing software. We conducted a systematic review of articles/websites about "Telemedicine," "Cybersecurity," and "Videoconferencing software.

"You Are Not My Type": An Evaluation of Classification Methods for Automatic Phytolith Identification.

Phytoliths can be an important source of information related to environmental and climatic change, as well as to ancient plant use by humans, particularly within the disciplines of paleoecology and archaeology. Currently, phytolith identification and categorization is performed manually by researchers, a time-consuming task liable to misclassifications. The automated classification of phytoliths would allow the standardization of identification processes, avoiding possible biases related to the classification capability of researchers.

Early and extremely early multi-label fault diagnosis in induction motors.

The detection of faulty machinery and its automated diagnosis is an industrial priority because efficient fault diagnosis implies efficient management of the maintenance times, reduction of energy consumption, reduction in overall costs and, most importantly, the availability of the machinery is ensured. Thus, this paper presents a new intelligent multi-fault diagnosis method based on multiple sensor information for assessing the occurrence of single, combined, and simultaneous faulty conditions in an induction motor. The contribution and novelty of the proposed method include the consideration of different physical magnitudes such as vibrations, stator currents, voltages, and rotational speed as a meaningful source of information of the machine condition.

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools.

The analysis of functional abilities and their development in early childhood (0-6 years old) are fundamental aspects among young children with certain types of developmental difficulties that can facilitate prevention, through programmed interventions adapted to the needs of each user (student or patient). There are, however, few investigations to date, that have analyzed the use of automated tools for recording and interpreting the results of the initial assessment. Here, a protocol is presented to examine the functional abilities in early childhood in young children, aged between 3-6 years old, with intellectual disabilities, but the protocol can also be used for ages 0 to 6 years.

Evaluation of Functional Abilities in 0-6 Year Olds: an Analysis with the eEarlyCare Computer Application.

The application of Industry 4.0 to the field of Health Sciences facilitates precise diagnosis and therapy determination. In particular, its effectiveness has been proven in the development of personalized therapeutic intervention programs.

Effectiveness of Blended Learning in Nursing Education.

Currently, teaching in higher education is being heavily developed by learning management systems that record the learning behaviour of both students and teachers. The use of learning management systems that include project-based learning and hypermedia resources increases safer learning, and it is proven to be effective in degrees such as nursing. In this study, we worked with 120 students in the third year of nursing degree.