Evaluation of spatial-temporal anomalies in the analysis of human movement

The dissemination of Internet of Things solutions, such as smartphones, lead to the appearance of devices that allow to monitor the activities of their users. In manufacture, the performed tasks consist on sets of predetermined movements that are exhaustively repeated, forming a repetitive behaviour. Additionally, there are planned and unplanned events on manufacturing production lines which cause the repetitive behaviour to stop. The execution of improper movements and the existence of events that might prejudice the productive system are regarded as anomalies. In this work, it was investigated the feasibility of the evaluation of spatial-temporal anomaly detection in the analysis of human movement. It is proposed a framework capable of detecting anomalies in generic repetitive time series, thus being adequate to handle Human motion from industrial scenarios. The proposed framework consists of (1) a new unsupervised segmentation algorithm; (2) feature extraction, selection and dimensionality reduction; (3) unsupervised classification based on DBSCAN used to distinguish normal and anomalous instances. The proposed solution was applied in four different datasets. Two of those datasets were synthetic and two were composed of real-world data, namely, electrocardiography data and human movement in manufacture. The yielded results demonstrated not only that anomaly detection in human motion is possible, but that the developed framework is generic and, with examples, it was shown that it may be applied in general repetitive time series with little adaptation effort for different domains. The results showed that the proposed framework has the potential to be applied in manufacturing production lines to monitor the employees movements, acting as a tool to detect both planned and unplanned events, and ultimately reduce the risk of appearance of musculoskeletal disorders in industrial settings in long-term

Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges

In recent years, new research has brought the field of EEG-based Brain-Computer Interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus on the development of practical BCI technologies that can be brought out of the lab and into real-world applications. In particular, we focus on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT). In pursuit of more practical BCIs for use outside of the lab, in this paper, we identify four application areas where disabled individuals could greatly benefit from advancements in BCI technology, namely,“Communication and Control”, “Motor Substitution”, “Entertainment”, and “Motor Recovery”. We review the current state of the art and possible future developments, while discussing the main research issues in these four areas. In particular, we expect the most progress in the development of technologies such as hybrid BCI architectures, user-machine adaptation algorithms, the exploitation of users’ mental states for BCI reliability and confidence measures, the incorporation of principles in human-computer interaction (HCI) to improve BCI usability, and the development of novel BCI technology including better EEG devices

Decoding Neural Signals with Computational Models: A Systematic Review of Invasive BMI

There are significant milestones in modern human's civilization in which mankind stepped into a different level of life with a new spectrum of possibilities and comfort. From fire-lighting technology and wheeled wagons to writing, electricity and the Internet, each one changed our lives dramatically. In this paper, we take a deep look into the invasive Brain Machine Interface (BMI), an ambitious and cutting-edge technology which has the potential to be another important milestone in human civilization. Not only beneficial for patients with severe medical conditions, the invasive BMI technology can significantly impact different technologies and almost every aspect of human's life. We review the biological and engineering concepts that underpin the implementation of BMI applications. There are various essential techniques that are necessary for making invasive BMI applications a reality. We review these through providing an analysis of (i) possible applications of invasive BMI technology, (ii) the methods and devices for detecting and decoding brain signals, as well as (iii) possible options for stimulating signals into human's brain. Finally, we discuss the challenges and opportunities of invasive BMI for further development in the area.Comment: 51 pages, 14 figures, review articl