Sensor-based artificial intelligence to support people with cognitive and physical disorders

A substantial portion of the world's population deals with disability. Many disabled people do not have equal access to healthcare, education, and employment opportunities, do not receive specific disability-related services, and experience exclusion from everyday life activities. One way to face these issues is through the use of healthcare technologies. Unfortunately, there is a large amount of diverse and heterogeneous disabilities, which require ad-hoc and personalized solutions. Moreover, the design and implementation of effective and efficient technologies is a complex and expensive process involving challenging issues, including usability and acceptability. The work presented in this thesis aims to improve the current state of technologies available to support people with disorders affecting the mind or the motor system by proposing the use of sensors coupled with signal processing methods and artificial intelligence algorithms. The first part of the thesis focused on mental state monitoring. We investigated the application of a low-cost portable electroencephalography sensor and supervised learning methods to evaluate a person's attention. Indeed, the analysis of attention has several purposes, including the diagnosis and rehabilitation of children with attention-deficit/hyperactivity disorder. A novel dataset was collected from volunteers during an image annotation task, and used for the experimental evaluation using different machine learning techniques. Then, in the second part of the thesis, we focused on addressing limitations related to motor disability. We introduced the use of graph neural networks to process high-density electromyography data for upper limbs amputees’ movement/grasping intention recognition for enabling the use of robotic prostheses. High-density electromyography sensors can simultaneously acquire electromyography signals from different parts of the muscle, providing a large amount of spatio-temporal information that needs to be properly exploited to improve recognition accuracy. The investigation of the approach was conducted using a recent real-world dataset consisting of electromyography signals collected from 20 volunteers while performing 65 different gestures. In the final part of the thesis, we developed a prototype of a versatile interactive system that can be useful to people with different types of disabilities. The system can maintain a food diary for frail people with nutrition problems, such as people with neurocognitive diseases or frail elderly people, which may have difficulties due to forgetfulness or physical issues. The novel architecture automatically recognizes the preparation of food at home, in a privacy-preserving and unobtrusive way, exploiting air quality data acquired from a commercial sensor, statistical features extraction, and a deep neural network. A robotic system prototype is used to simplify the interaction with the inhabitant. For this work, a large dataset of annotated sensor data acquired over a period of 8 months from different individuals in different homes was collected. Overall, the results achieved in the thesis are promising, and pave the way for several real-world implementations and future research directions

Internal markets for knowledge-intensive human resources: a new frontier in personalization strategy for knowledge management

Purpose \u2013 This paper aims to develop a conceptual framework of an integrated knowledge management system, in which several knowledge management strategies are nested. Specifically, the paper focuses on possible strategies to localise and transfer different types of knowledge resources in project-based organisations, including expertise embedded in talented people, in order to pursue new emerging business opportunities and improve the whole organisation\u2019s effectiveness. Design/methodology/approach \u2013 This paper is theoretical in nature. Drawing on the literature on the management of tacit knowledge in project-based organisations and on internal knowledge markets we introduce the conceptual framework for an internal knowledge market which may suit the context of project-based organisations. We also briefly discuss some organisational and managerial issues potentially connected to internal knowledge market development. Originality/value \u2013 The originality of the paper lies in assuming different motivational drivers, currencies and market structures for the different kinds of knowledge goods that can be exchanged in a complex organisational structure, such as a large project-based organisation. By focussing on the internal trade of knowledge-intensive human resources, i.e. a strategic knowledge good for project-based organisations, we aim to address a specific gap in the management literature. In fact, the literature, while recognising that managing knowledge-intensive resources is a critical issue in project-based organisations, largely neglects the market-based approach to deal with it. Practical implications \u2013 Although this paper is theoretical in nature, it provides some guidelines for the development of internal markets for knowledge intensive resources, defining contexts of application, roles of the different actors, working mechanisms as well as organizational and managerial tools to mitigate possible risks and enhance benefits

Opening up innovation processes through contests in the food sector

Purpose: The purpose of this paper is to investigate how an adequate mix of technological, organisational and managerial tools might support Open Innovation (OI) processes achieved by contests in the food sector. Design/methodology/approach: The methodology of this paper is exploratory in nature. Data have been gathered about the 140 innovation contests launched by the best global food brands (2013 BusinessWeek/Interbrand Best Global Brands) over the last decade. Findings: The research highlights the main changes that have occurred over the last decade, showing that the choice of platform type for contest launches is often neglected or considered as an ancillary element. Indeed, it is a choice that embeds another set of technological, organisational and managerial tools that strongly influence the collaborative behaviour (and the participation itself) of partners throughout the innovation process. Research limitations/implications: Companies investigated in this paper consist exclusively of top brands in the sector. Future research should strive to obtain larger samples, develop a set of fine-grained hypotheses, and test them by using appropriate statistical techniques. Originality/value: This paper fills an inexplicable gap in academic literature due to the fact that food companies are those that mainly use contests in order to implement OI but they are scarcely researched regarding this issue

“Il più bello gabinetto delle stampe che esiste”: a (failed) project for the Ortalli collection of prints at the Biblioteca Palatina in Parma

After having been valued mainly as conveyors of visual information, prints in nineteenth-century western Europe came to be recognised as works of art. In some cases this led to a reconsideration of the location of print collections in public institutions, but moving them was not always easy. This article reconstructs Paul J. Kristeller’s (failed) project to hand over Ortalli albums of prints from the Biblioteca Palatina to the royal art museum in Parma (1893–1898) by tracing arguments used to support or oppose the relocation. By studying local events in the context of a national plan designed to reorganise print collections following foreign examples, the article shows the extent to which the status of prints and print collections grounded the Palatina director’s opposition to the project, and how this contributed to the preservation of the collection’s historical memory and the shaping of current frameworks of public print collections in Italy

From the reliure mobile to the Schraubband. Collecting and storing prints in adjustable albums at the Kupferstichkabinett in Berlin

A large section of the print holdings of the Kupferstichkabinett in Berlin is housed in bulky albums known as Schraubbände (‘screw volumes’). From the outside, these albums are similar to print albums that abounded in private collections before the nineteenth century. But their leaves are not sewn together as in a traditional codex structure; rather, they are screwed together between metal rods. The rods can be unscrewed for easy insertion and removal of the mounted prints, while keeping them in the given order. By investigating material and historical aspects of the Berlin Schraubbände, this paper identifies their forerunners in the reliure mobile-albums in use at the Bibliothèque nationale in Paris, proposes a rationale behind their use at the Kupferstichkabinett in the late nineteenth century, and challenges the traditional discrimination between bound and unbound print collections

High-Field Electron Paramagnetic Resonance Reveals a Stable Glassy Fraction up to Melting in Semicrystalline Poly(dimethylsiloxane)

The reorientation of the guest 4-methoxy-TEMPO (spin probe) in the disordered fraction of semicrystalline poly(dimethylsiloxane) (PDMS) is investigated by high-field electron paramagnetic resonance (HF-EPR) at 190 and 285 GHz. Accurate numerical simulations of the HF-EPR lineshapes evidence that the reorientation times of the spin probes are distributed between the melting temperature Tm and Tm-30 K. The distribution exhibits, in addition to a broad component, a narrow component with low mobility up to the PDMS melting point. It is shown that the temperature dependence of the reorientation time of the spin probes with low mobility is the same of the spin probes in glassy PDMS. The result suggests that the low-mobility fraction is localized in the so-called rigid amorphous fraction

Local Reversible Melting in Semicrystalline Poly(dimethylsiloxane): A High-Field Electron Paramagnetic Resonance Study

The reorientation of the paramagnetic guest 4-methoxy-TEMPO (spin probe) in the disordered fraction of semicrystalline poly(dimethylsiloxane) (PDMS) is investigated by high-field electron paramagnetic resonance (HF-EPR) at 190 and 285 GHz. The distribution of reorientation times is evidenced by accurate numerical simulations of the HF-EPR line shapes above 200 K. The distribution exhibits a bimodal structure with (i) a broad component corresponding to spin probes with fast and intermediate mobility located in the disordered fraction far from the crystallites and (ii) a narrow component corresponding to spin probes with extremely low mobility trapped close to the crystallites in a glassy environment persisting up to the PDMS melting. The spin probe undergoes an exchange process between the trapped and the more mobile fractions which is accounted for by an equilibrium reversible process with standard Gibbs free energy of reaction per spin probe mole Î\u94Gr0 â\u89\u83 4(Î\u94Hm - TÎ\u94Sm), where Î\u94Sm is the equilibrium melting entropy per monomer mole following the absorption of the heat Î\u94Hm. The process is interpreted as signature of reversible tertiary nucleation, occurring at the intersection of crystalline surfaces, thus suggesting surface roughness of the crystal-amorphous interface. It becomes thermodynamically favored at temperatures higher than T â\u88¼ 209 K where the onset of PDMS melting is located according to differential scanning calorimetry

Recognition of cooking activities through air quality sensor data for supporting food journaling

Abstract Unhealthy behaviors regarding nutrition are a global risk for health. Therefore, the healthiness of an individual's nutrition should be monitored in the medium and long term. A powerful tool for monitoring nutrition is a food diary; i.e., a daily list of food taken by the individual, together with portion information. Unfortunately, frail people such as the elderly have a hard time filling food diaries on a continuous basis due to forgetfulness or physical issues. Existing solutions based on mobile apps also require user's effort and are rarely used in the long term, especially by elderly people. For these reasons, in this paper we propose a novel architecture to automatically recognize the preparation of food at home in a privacy-preserving and unobtrusive way, by means of air quality data acquired from a commercial sensor. In particular, we devised statistical features to represent the trend of several air parameters, and a deep neural network for recognizing cooking activities based on those data. We collected a large corpus of annotated sensor data gathered over a period of 8 months from different individuals in different homes, and performed extensive experiments. Moreover, we developed an initial prototype of an interactive system for acquiring food information from the user when a cooking activity is detected by the neural network. To the best of our knowledge, this is the first work that adopts air quality sensor data for cooking activity recognition