Locomotion Traces Data Mining for Supporting Frail People with Cognitive Impairment

The rapid increase in the senior population is posing serious challenges to national healthcare systems. Hence, innovative tools are needed to early detect health issues, including cognitive decline. Several clinical studies show that it is possible to identify cognitive impairment based on the locomotion patterns of older people. Thus, this thesis at first focused on providing a systematic literature review of locomotion data mining systems for supporting Neuro-Degenerative Diseases (NDD) diagnosis, identifying locomotion anomaly indicators and movement patterns for discovering low-level locomotion indicators, sensor data acquisition, and processing methods, as well as NDD detection algorithms considering their pros and cons. Then, we investigated the use of sensor data and Deep Learning (DL) to recognize abnormal movement patterns in instrumented smart-homes. In order to get rid of the noise introduced by indoor constraints and activity execution, we introduced novel visual feature extraction methods for locomotion data. Our solutions rely on locomotion traces segmentation, image-based extraction of salient features from locomotion segments, and vision-based DL. Furthermore, we proposed a data augmentation strategy to increase the volume of collected data and generalize the solution to different smart-homes with different layouts. We carried out extensive experiments with a large real-world dataset acquired in a smart-home test-bed from older people, including people with cognitive diseases. Experimental comparisons show that our system outperforms state-of-the-art methods

Innovative Technologies and Services for Smart Cities

A smart city is a modern technology-driven urban area which uses sensing devices, information, and communication technology connected to the internet of things (IoTs) for the optimum and efficient utilization of infrastructures and services with the goal of improving the living conditions of citizens. Increasing populations, lower budgets, limited resources, and compatibility of the upgraded technologies are some of the few problems affecting the implementation of smart cities. Hence, there is continuous advancement regarding technologies for the implementation of smart cities. The aim of this Special Issue is to report on the design and development of integrated/smart sensors, a universal interfacing platform, along with the IoT framework, extending it to next-generation communication networks for monitoring parameters of interest with the goal of achieving smart cities. The proposed universal interfacing platform with the IoT framework will solve many challenging issues and significantly boost the growth of IoT-related applications, not just in the environmental monitoring domain but in the other key areas, such as smart home, assistive technology for the elderly care, smart city with smart waste management, smart E-metering, smart water supply, intelligent traffic control, smart grid, remote healthcare applications, etc., signifying benefits for all countries

On the Recognition of Emotion from Physiological Data

This work encompasses several objectives, but is primarily concerned with an experiment where 33 participants were shown 32 slides in order to create ‗weakly induced emotions‘. Recordings of the participants‘ physiological state were taken as well as a self report of their emotional state. We then used an assortment of classifiers to predict emotional state from the recorded physiological signals, a process known as Physiological Pattern Recognition (PPR). We investigated techniques for recording, processing and extracting features from six different physiological signals: Electrocardiogram (ECG), Blood Volume Pulse (BVP), Galvanic Skin Response (GSR), Electromyography (EMG), for the corrugator muscle, skin temperature for the finger and respiratory rate. Improvements to the state of PPR emotion detection were made by allowing for 9 different weakly induced emotional states to be detected at nearly 65% accuracy. This is an improvement in the number of states readily detectable. The work presents many investigations into numerical feature extraction from physiological signals and has a chapter dedicated to collating and trialing facial electromyography techniques. There is also a hardware device we created to collect participant self reported emotional states which showed several improvements to experimental procedure

Disrupting the Digital Humanities

All too often, defining a discipline becomes more an exercise of exclusion than inclusion. Disrupting the Digital Humanities seeks to rethink how we map disciplinary terrain by directly confronting the gatekeeping impulse of many other so-called field-defining collections. What is most beautiful about the work of the Digital Humanities is exactly the fact that it can’t be tidily anthologized. In fact, the desire to neatly define the Digital Humanities (to filter the DH-y from the DH) is a way of excluding the radically diverse work that actually constitutes the field. This collection, then, works to push and prod at the edges of the Digital Humanities — to open the Digital Humanities rather than close it down. Ultimately, it’s exactly the fringes, the outliers, that make the Digital Humanities both heterogeneous and rigorous. This collection does not constitute yet another reservoir for the new Digital Humanities canon. Rather, its aim is less about assembling content as it is about creating new conversations. Building a truly communal space for the digital humanities requires that we all approach that space with a commitment to: 1) creating open and non-hierarchical dialogues; 2) championing non-traditional work that might not otherwise be recognized through conventional scholarly channels; 3) amplifying marginalized voices; 4) advocating for students and learners; and 5) sharing generously and openly to support the work of our peers

Social work with airports passengers

Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically

Disrupting the Digital Humanities

All too often, defining a discipline becomes more an exercise of exclusion than inclusion. Disrupting the Digital Humanities seeks to rethink how we map disciplinary terrain by directly confronting the gatekeeping impulse of many other so-called field-defining collections. What is most beautiful about the work of the Digital Humanities is exactly the fact that it can’t be tidily anthologized. In fact, the desire to neatly define the Digital Humanities (to filter the DH-y from the DH) is a way of excluding the radically diverse work that actually constitutes the field. This collection, then, works to push and prod at the edges of the Digital Humanities — to open the Digital Humanities rather than close it down. Ultimately, it’s exactly the fringes, the outliers, that make the Digital Humanities both heterogeneous and rigorous. This collection does not constitute yet another reservoir for the new Digital Humanities canon. Rather, its aim is less about assembling content as it is about creating new conversations. Building a truly communal space for the digital humanities requires that we all approach that space with a commitment to: 1) creating open and non-hierarchical dialogues; 2) championing non-traditional work that might not otherwise be recognized through conventional scholarly channels; 3) amplifying marginalized voices; 4) advocating for students and learners; and 5) sharing generously and openly to support the work of our peers