Filippo Cavallo

Assessment of walking features from foot inertial sensing

An ambulatory monitoring system is developed for the estimation of spatio-temporal gait parameters. The inertial measurement unit embedded in the system is composed of one biaxial accelerometer and one rate gyroscope, and it reconstructs the sagittal trajectory of a sensed point on the instep of the foot. A gait phase segmentation procedure is devised to determine temporal gait parameters, including stride time and relative stance; the procedure allows to define the time intervals needed for carrying an efficient implementation of the strapdown integration, which allows to estimate stride length, walking speed, and incline. The measurement accuracy of walking speed and inclines assessments is evaluated by experiments carried on adult healthy subjects walking on a motorized treadmill. Root-mean-square errors less than 0.18 km/h (speed) and 1.52% (incline) are obtained for tested speeds and inclines varying in the intervals [3, 6] km/h and [-5, +15]%, respectively. Based on the results of these experiments, it is concluded that foot inertial sensing is a promising tool for the reliable identification of subsequent gait cycles and the accurate assessment of walking speed and incline.

A step toward GPS/INS personal navigation systems: real-time assessment of gait by foot inertial sensing

In this paper, we develop a system for which applications in the field of personal navigation are planned. In the current version, the system embodies a Global Positioning System (GPS) receiver and an inertial measurement unit (IMU), composed of two dual-axis accelerometers and one single-axis gyro. The IMU is positioned at a subjects foot instep, and it is intended to produce estimates of some gait parameters, including stride length, stride time, and walking speed. Data from GPS and IMU are managed by a DSP-based control box. The computations performed by the DSP processor allow to detect subsequent foot contacts by a threshold-based method applied to gyro signal, and to reconstruct the trajectory of the foot instep by numerical strapdown integration. Features of human walking dynamics are incorporated in the algorithm to enhance the estimation accuracy against errors due to sensor noise and integration drift. All computations are performed by the DSP processor in real-time conditions. The foot sensor performance is assessed during outdoor level walking trials. The traveled distance estimated by inertial dead-reckoning is compared with the estimate produced by GPS in experimental conditions where GPS can be used as a reference source for accurate absolute positioning. Results show the remarkable accuracy achieved by foot inertial sensing.

Development of a Socially Believable Multi-Robot Solution from Town to Home

Abstract Technological advances in the robotic and ICT fields represent an effective solution to address specific societal problems to support ageing and independent life. One of the key factors for these technologies is that they have to be socially acceptable and believable to the end-users. This paper aimed to present some technological aspects that have been faced to develop the Robot-Era system, a multi-robotic system that is able to act in a socially believable way in the environments daily inhabited by humans, such as urban areas, buildings and homes. In particular, this paper focuses on two services—shopping delivery and garbage collection—showing preliminary results on experiments conducted with 35 elderly people. The analysis adopts an end-user-oriented perspective, considering some of the main attributes of acceptability: usability, attitude, anxiety, trust and quality of life.

A Cloud Robotics Solution to Improve Social Assistive Robots for Active and Healthy Aging

Technological innovation in robotics and ICT represents an effective solution to tackle the challenge of providing social sustainable care services for the ageing population. The recent introduction of cloud technologies is opening new opportunities for the provisioning of advanced robotic services based on the cooperation of a number of connected robots, smart environments and devices improved by the huge cloud computational and storage capability. In this context, this paper aims to investigate and assess the potentialities of a cloud robotic system for the provisioning of assistive services for the promotion of active and healthy ageing. The system comprised two different smart environments, located in Italy and Sweden, where a service robot is connected to a cloud platform for the provisioning of localization based services to the users. The cloud robotic services were tested in the two realistic environments to assess the general feasibility of the solution and demonstrate the ability to provide assistive location based services in a multiple environment framework. The results confirmed the validity of the solution but also suggested a deeper investigation on the dependability of the communication technologies adopted in such kind of systems.

ENDOCAS NAVIGATOR PLATFORM: A COMMON PLATFORM FOR COMPUTER AND ROBOTIC ASSISTANCE IN MINIMALLY INVASIVE SURGERY.

Computer‐assisted surgery (CAS) systems are currently used in only a few surgical specialties: ear, nose and throat (ENT), neurosurgery and orthopaedics. Almost all of these systems have been developed as dedicated platforms and work on rigid anatomical structures. The development of augmented reality systems for intra‐abdominal organs remains problematic because of the anatomical complexity of the human peritoneal cavity and especially because of the deformability of its organs. The aim of the present work was to develop and implement a highly modular platform (targeted for minimally invasive laparoscopic surgery) generally suitable for CAS, and to produce a prototype for demonstration of its potential clinical application and use in laparoscopic surgery.

Recognition of Daily Gestures with Wearable Inertial Rings and Bracelets

Recognition of activities of daily living plays an important role in monitoring elderly people and helping caregivers in controlling and detecting changes in daily behaviors. Thanks to the miniaturization and low cost of Microelectromechanical systems (MEMs), in particular of Inertial Measurement Units, in recent years body-worn activity recognition has gained popularity. In this context, the proposed work aims to recognize nine different gestures involved in daily activities using hand and wrist wearable sensors. Additionally, the analysis was carried out also considering different combinations of wearable sensors, in order to find the best combination in terms of unobtrusiveness and recognition accuracy. In order to achieve the proposed goals, an extensive experimentation was performed in a realistic environment. Twenty users were asked to perform the selected gestures and then the data were off-line analyzed to extract significant features. In order to corroborate the analysis, the classification problem was treated using two different and commonly used supervised machine learning techniques, namely Decision Tree and Support Vector Machine, analyzing both personal model and Leave-One-Subject-Out cross validation. The results obtained from this analysis show that the proposed system is able to recognize the proposed gestures with an accuracy of 89.01% in the Leave-One-Subject-Out cross validation and are therefore promising for further investigation in real life scenarios.

Ambient Assisted Living and ageing: Preliminary results of RITA project

The ageing of population is a social phenomenon that most of worldwide countries are facing. They are, and will be even more in the future, indeed trying to find solutions for improving quality of life of their elderly citizens. The project RITA wants to demonstrate that an update of the current socio-medical services with an Ambient Assisted Living (AAL) approach could improve the service efficiency and the quality of life of both elderly and caregiver. This paper presents the preliminary results obtained in RITA.

Smartphone-Based Food Diagnostic Technologies: A Review

A new generation of mobile sensing approaches offers significant advantages over traditional platforms in terms of test speed, control, low cost, ease-of-operation, and data management, and requires minimal equipment and user involvement. The marriage of novel sensing technologies with cellphones enables the development of powerful lab-on-smartphone platforms for many important applications including medical diagnosis, environmental monitoring, and food safety analysis. This paper reviews the recent advancements and developments in the field of smartphone-based food diagnostic technologies, with an emphasis on custom modules to enhance smartphone sensing capabilities. These devices typically comprise multiple components such as detectors, sample processors, disposable chips, batteries and software, which are integrated with a commercial smartphone. One of the most important aspects of developing these systems is the integration of these components onto a compact and lightweight platform that requires minimal power. To date, researchers have demonstrated several promising approaches employing various sensing techniques and device configurations. We aim to provide a systematic classification according to the detection strategy, providing a critical discussion of strengths and weaknesses. We have also extended the analysis to the food scanning devices that are increasingly populating the Internet of Things (IoT) market, demonstrating how this field is indeed promising, as the research outputs are quickly capitalized on new start-up companies.

Technology and Innovative Services

The last century handed us a considerably older population, particularly in the developed countries. Life expectancy which in the industrialized countries at the beginning of the 1900s was barely 47 years, has progressively increased, and today it is almost 80 years, with women in an advantageous position. Moreover, the real qualitative leap is represented by the conditions in which aging takes place, conditions that until now were inconceivable for past generations, such as the level of education, the health status, and the economic re sources of aging individuals.

A first step toward a pervasive and smart ZigBee sensor system for assistance and rehabilitation

This paper shows the general concept and the primary implementation of a pervasive intelligent system for rehabilitation. The scope of this work is to highlight the possibility to join two important research fields, i.e. rehabilitation and ambient assisted living, to enhance the capabilities and independence of disable and aged people. The described system was composed of a ZigBee network, with coordinator, sensor and actuator nodes, able to identify and control patients activities and send warning to caregiver if requests in warning functionality, and of a software interface to manage the whole network and to monitor patient in outdoor environment.