Evaluation of functional tests performance using a camera-based and machine learning approach.

The objective of this study is to evaluate the performance of functional tests using a camera-based system and machine learning techniques. Specifically, we investigate whether OpenPose and any standard camera can be used to assess the quality of the Single Leg Squat Test and Step Down Test functional tests. We recorded these exercises performed by forty-six healthy subjects, extract motion data, and classify them to expert assessments by three independent physiotherapists using 15 binary parameters. We calculated ranges of movement in Keypoint-pair orientations, joint angles, and relative distances of the monitored segments and used machine learning algorithms to predict the physiotherapists' assessments. Our results show that the AdaBoost classifier achieved a specificity of 0.8, a sensitivity of 0.68, and an accuracy of 0.7. Our findings suggest that a camera-based system combined with machine learning algorithms can be a simple and inexpensive tool to assess the performance quality of functional tests.

Information System for Integration of Genetic Information and Clinical Knowledge.

This paper deals with a developed information system called a Personal Genetic Card (PGC). The system aims to integrate the known clinical knowledge (interpretations and recommendations) linked to genetic information with the analysis results of a patient. Genetic information has an increasing influence on the clinical decision of physicians as well as other medical and health services. All these services need to connect the genetic profile with the phenotypes such as drug metabolization, drug toxicity, drug dosing, or intolerance of some substances. It still applies that the best way to represent data of medical records is a structured form of record. Many approaches can be used to define the structure (syntax) of the record and the content (semantics) of the record and to exchange data in forms of various standards and terminologies. Moreover, the genetic analysis field has its terminology databases for representing genetic information (e.g. HGNC, NCBI). The next step is to connect the genetic analysis results with c clinical knowledge (interpretation, recommendation). This step is crucial because the genetic analysis results have clinical benefits if we can assign them to some valid clinical knowledge. And the best final result is when we can make a better recommendation based on the genetic results and clinical knowledge. Genetic knowledge databases (e.g. PharmGKB, SNPedia, ClinVar) contain many interpretations and even recommendations for genetic analysis results based on different purposes. This situation is appropriate for developing the PGC system that takes inspiration from case-based reasoning in purpose to allow integration of the assumptions and knowledge about phenotypes and the real genetic analysis results in the structured form.

Intracranial electrophysiological recordings from the human brain during memory tasks with pupillometry.

Data comprise intracranial EEG (iEEG) brain activity represented by stereo EEG (sEEG) signals, recorded from over 100 electrode channels implanted in any one patient across various brain regions. The iEEG signals were recorded in epilepsy patients (N = 10) undergoing invasive monitoring and localization of seizures when they were performing a battery of four memory tasks lasting approx. 1 hour in total. Gaze tracking on the task computer screen with estimating the pupil size was also recorded together with behavioral performance. Each dataset comes from one patient with anatomical localization of each electrode contact. Metadata contains labels for the recording channels with behavioral events marked from all tasks, including timing of correct and incorrect vocalization of the remembered stimuli. The iEEG and the pupillometric signals are saved in BIDS data structure to facilitate efficient data sharing and analysis.

Automatic Telerehabilitation System in a Home Environment Using Computer Vision.

In this paper, we follow up on research dealing with body tracking and motor rehabilitation. We describe the current situation in telerehabilitation in the home environment. Existing solutions do not allow wide adoption due to hardware requirements and complicated setup. We come with the possibility of telerehabilitation using only laptop or mobile web camera. Together with physiotherapists, we have compiled a set of complex motor exercises to show that the system can be practically used.

Author Correction: Pupil size reflects successful encoding and recall of memory in humans.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Affordable Personalized, Immersive VR Motor Rehabilitation System with Full Body Tracking.

During the last decade, we have experienced fast development of virtual reality technology combined with various sensors and applications in different fields. The devices and applications are more easily accessible for the broader public. In this article, we describe a feasibility study of an affordable personalized, immersive VR motor rehabilitation system with full body tracking. While virtual reality rehabilitation is a relatively new field, several applications were already proven more effective than traditional rehabilitation programs. The applied methods utilize VR headset HTC Vive and HTC trackers together witch inverse kinematics algorithms to provide full body tracking. For that, we provide a framework for individual body calibration. The main result of the study is a developed virtual environment with guided rehabilitation scenarios based on personalized body calibration. We have proven that this approach can be used in personalized rehabilitation programs.

Personalized Monitoring and Assistive Systems: Case Study of Efficient Home Solutions.

The rapid emergence and proliferation of connected medical devices and their application in healthcare are already part of the Healthcare Internet of Things (IoT) - as this area started to be named. Their true impact on patient care and other aspects of healthcare remains to be seen and is highly dependent on the quality and relevancy of the data acquired. There is also the trend of application of IoT in telemedicine and home care environment. Currently many research groups focus on design and development of various solutions that can assist elderly and handicapped people in their home environment. However, many of these solutions are sophisticated and require advanced users that are able to control the device, handle error states and exceptions. They are frequently using expensive technologies that are good for laboratory environment but they are not affordable for many elderly or handicapped persons. In the paper we will analyze the current situation, present identified needs of elderly population and propose potential solutions. On a case study of efficient home solution of a personalized and assistive system we will show possibilities of technologically simple solutions using off-the-shelf devices and elements.

Pupil size reflects successful encoding and recall of memory in humans.

Pupil responses are known to indicate brain processes involved in perception, attention and decision-making. They can provide an accessible biomarker of human memory performance and cognitive states in general. Here we investigated changes in the pupil size during encoding and recall of word lists. Consistent patterns in the pupil response were found across and within distinct phases of the free recall task. The pupil was most constricted in the initial fixation phase and was gradually more dilated through the subsequent encoding, distractor and recall phases of the task, as the word items were maintained in memory. Within the final recall phase, retrieving memory for individual words was associated with pupil dilation in absence of visual stimulation. Words that were successfully recalled showed significant differences in pupil response during their encoding compared to those that were forgotten - the pupil was more constricted before and more dilated after the onset of word presentation. Our results suggest pupil size as a potential biomarker for probing and modulation of memory processing.