Mario Caruso

Assistive Device With Conventional, Alternative, and Brain-Computer Interface Inputs to Enhance Interaction With the Environment for People With Amyotrophic Lateral Sclerosis: A Feasibility and Usability Study

OBJECTIVE To evaluate the feasibility and usability of an assistive technology (AT) prototype designed to be operated with conventional/alternative input channels and a P300-based brain-computer interface (BCI) in order to provide users who have different degrees of muscular impairment resulting from amyotrophic lateral sclerosis (ALS) with communication and environmental control applications. DESIGN Proof-of-principle study with a convenience sample. SETTING An apartment-like space designed to be fully accessible by people with motor disabilities for occupational therapy, placed in a neurologic rehabilitation hospital. PARTICIPANTS End-users with ALS (N=8; 5 men, 3 women; mean age ± SD, 60 ± 12 y) recruited by a clinical team from an ALS center. INTERVENTIONS Three experimental conditions based on (1) a widely validated P300-based BCI alone; (2) the AT prototype operated by a conventional/alternative input device tailored to the specific end-users residual motor abilities; and (3) the AT prototype accessed by a P300-based BCI. These 3 conditions were presented to all participants in 3 different sessions. MAIN OUTCOME MEASURES System usability was evaluated in terms of effectiveness (accuracy), efficiency (written symbol rate, time for correct selection, workload), and end-user satisfaction (overall satisfaction) domains. A comparison of the data collected in the 3 conditions was performed. RESULTS Effectiveness and end-user satisfaction did not significantly differ among the 3 experimental conditions. Condition III was less efficient than condition II as expressed by the longer time for correct selection. CONCLUSIONS A BCI can be used as an input channel to access an AT by persons with ALS, with no significant reduction of usability.

The homes of tomorrow: service composition and advanced user interfaces

Home automation represents a growing market in the industrialized world. Today’s systems are mainly based on ad hoc and proprietary solutions, with little to no interoperability and smart integration. However, in a not so distant future, our homes will be equipped with many sensors, actuators and devices, which will collectively expose services, able to smartly interact and integrate, in order to offer complex services providing even richer functionalities. In this paper we present the approach and results of SM4ALLSmart hoMes for All, a project investigating automatic service composition and advanced user interfaces applied to domotics.

Service Ecologies for Home/Building Automation

Abstract Service ecologies are networks of services pervasively embedded in everyday environments, e.g., smart homes, where they are composed and orchestrated in order to provide advanced functionalities. In this paper, we show how the interplay of off-line and on-line composition of services can improve flexibility and adaptiveness.

Synthesizing daily life logs through gaming and simulation

In the recent years there has been a growing interest in the design and implementation of smart homes, and smart buildings in general. The evaluation of approaches in this area typically requires massive datasets of measurements from deployed sensors in real prototypes. While a few datasets obtained by real smart homes are freely available, they are not sufficient for comparing different approaches and techniques in a variety of configurations. In this work, we propose a smart home dataset generation strategy based on a simulated environment populated with virtual autonomous agents, sensors and devices which allow to customize and reproduce a smart space using a series of useful parameters. The simulation is based on declarative process models for modeling habits performed by agents, an action theory for realizing low-level atomic actions, and a 3D virtual execution environment. We show how different configurations generate a variety of sensory logs that can be used as input to a state-of-the-art activity recognition technique in order to evaluate its performance under parametrized scenarios, as well as provide guidelines for actually building real smart homes.

My-world-in-my-tablet: an architecture for people with physical impairment

Mobile computing, coupled with advanced types of input interfaces, such as Brain Computer Interfaces (BCIs), and smart spaces can improve the quality of life of persons with disabilities. In this paper, we describe the architecture and the prototype of an assistive system, which allows users to express themselves and partially preserve their independence in controlling electrical devices at home. Even in absence of muscular functions, the proposed system would still allow the user some communication and control capabilities, by relying on non-invasive BCIs. Experiments show how the fully-software realization of the system guarantees effective use with BCIs.

Micro-accounting for Optimizing and Saving Energy in Smart Buildings

Energy management, and in particular its optimization, is one of the hot trends in the current days, both at the enterprise level (optimization of whole corporate/government buildings) and single-citizens’ homes. The current trend is to provide knowledge about the micro(scopic) energy consumption. This allows to save energy, but also to optimize the different energy sources (e.g., solar vs. traditional one) in case of a mixed architecture. In this work, after briefly introducing our specific platform for smart environments able to micro-account energy consumption of devices, we present two case studies of its utilization: energy saving in offices and smart switching among different energy sources.

On the Black-Box Stand-by Recognition Strategies in Smart Homes Environments

The number of smart devices connected h24 to the electric plant of an house is continuously growing with a clear impact on the energy consumption footprint. In the near future the stand-by consumption of these appliances will represent about the 15% of the total house consumption, a remarkable percentage intended to increase due to the growing number of smart devices contained in the house of tomorrow. In the presented scenario smart houses play an important role to reduce the stand-by consumption footprint introducing new strategies able to autonomously recognize these energy wastes. In 1999 the International Energy Agency launched the one-watt initiative with the aim of fighting this problem, todays smart homes can contribute to reduce the phenomenon with a 60% saving. Different strategies can be used in order to recognize a stand-by state, they can be divided in supervised and unsupervised approaches. In this paper we present an algorithm for each kind of approach comparing the performance of the two single approaches with the aim of proving that unsupervised techniques are ready to be widely adopted. An experimental evaluation concludes the paper.