“BEDRUNN3R: An Intelligent Running Alarm Clock”

The conventional alarm clocks have been serving their purpose to mankind since their inception, to wake people up every single morning. However, the rates of oversleeping are still on the rise and people are having trouble waking up in the morning even with the use of alarm clocks. The snooze button that is available on all conventional alarm clocks provide user with more sleep but at a cost of deteriorating their quality of health and exacerbating sleep inertia at the same time. The objective of this project is to study the problems associated with sleep that are often faced by people and to conduct a comparative study on existing intelligent alarm clocks in the market that functions using movement. Then, to solve the problems studied, an intelligent moving alarm clock that implements the application of artificial intelligence will be developed. The prototype of this alarm clock will also be tested against the usage of traditional and conventional alarm clocks. The Hypothetico-Deductive method will be used as the development methodology of this project and the prototyping phase will be following the Rapid Application Development (RAD) model. The development methodology will be used alongside some other research methodologies to develop the system flows and architectures. The V-Model will be used to evaluate the performance and viability of the system in the real-world environment. The test results will indicate the effectiveness of the system to determine if it surpasses the conventional alarm clocks and can be used as a replacement. The test cases will be designed using different room architectures and different situations in order to make sure all aspects and factors are tested

Intelligent Biosignal Analysis Methods

This book describes recent efforts in improving intelligent systems for automatic biosignal analysis. It focuses on machine learning and deep learning methods used for classification of different organism states and disorders based on biomedical signals such as EEG, ECG, HRV, and others

MECHANISMS OF MEMORY CONSOLIDATION

Extensive research has shown that sleep supports memory. Newer work suggests that wakefulness can also benefit retention of new information. However, the exact mechanisms which govern memory consolidation in sleep and wake are largely unknown. The implementation of new technologies, which draw on these natural memory processes, allows some insight into their characteristics. This work aims at elucidating some aspects of memory consolidation processes in the realm of sleep and wake. Firstly, we train novel non-words, a material previously indicated to benefit from sleep-associated consolidation, with explicit and implicit methods to determine whether the implicit learning (via the Hebb repetition task) would facilitate lexical integration independently of sleep. The results reveal that lexical integration of novel words is contingent on a good level of explicit training, followed by a consolidation delay with sleep. We speculate that sleep-associated consolidation may be mediated by the degree of overlap between new and already known material. To further capitalise on these findings, we test whether applying non-verbal cues during sleep can improve learning of novel words and their integration within the lexicon using Targeted Memory Reactivation (TMR) paradigm. Our results indicate that reactivating novel lexical representations in sleep improves their consolidation and facilitates their recall. However, the lack of lexical integration observed suggests the need for future research. Finally, based on recent evidence that quiet wakeful rest can result in comparable memory increases to sleep, we explore the consolidation during awake state using transcranial direct current stimulation (tDCS). We found that applying tDCS to the right occipital-parietal site enhances memory for a list of words as compared to no stimulation. The findings imply that memory consolidation during quiet wakefulness can be manipulated externally, which may direct future research. Nevertheless, the exact neuro-correlates of memory consolidation in quiet wake are yet to be fully investigated

Measuring Behavior 2018 Conference Proceedings

These proceedings contain the papers presented at Measuring Behavior 2018, the 11th International Conference on Methods and Techniques in Behavioral Research. The conference was organised by Manchester Metropolitan University, in collaboration with Noldus Information Technology. The conference was held during June 5th – 8th, 2018 in Manchester, UK. Building on the format that has emerged from previous meetings, we hosted a fascinating program about a wide variety of methodological aspects of the behavioral sciences. We had scientific presentations scheduled into seven general oral sessions and fifteen symposia, which covered a topical spread from rodent to human behavior. We had fourteen demonstrations, in which academics and companies demonstrated their latest prototypes. The scientific program also contained three workshops, one tutorial and a number of scientific discussion sessions. We also had scientific tours of our facilities at Manchester Metropolitan Univeristy, and the nearby British Cycling Velodrome. We hope this proceedings caters for many of your interests and we look forward to seeing and hearing more of your contributions