Simone Valenti

A High Reliability Wearable Device for Elderly Fall Detection

Falls are critical events among elderly people that requires timely rescue. In this paper, we propose a fall detection system consisting of an inertial unit that includes triaxial accelerometer, gyroscope, and magnetometer with efficient data fusion and fall detection algorithms. Starting from the raw data, the implemented orientation filter provides the correct orientation of the subject in terms of yaw, pitch, and roll angles. The system is tested according to experimental protocols, engaging volunteers who performed simulated falls, simulated falls with recovery, and activities of daily living. By placing our wearable sensor on the waist of the subject, the unit is able to achieve fall detection performance above those of similar systems proposed in literature. The results obtained through commonly adopted protocols show excellent accuracy, sensitivity and specificity, improving the results of other techniques proposed in the literature.

A Wearable Fall Detector for Elderly People Based on AHRS and Barometric Sensor

Falls and their consequences are among the major health care problems affecting functional mobility and quality of life of elderly people. Even for people living independently, falls are common occurrences. In this paper, we present a waist-mounted device useful to detect possible falls in elderly people. Through data coming from a three-axis accelerometer, a three-axis gyroscope, a three-axis magnetometer, and a barometer sensor integrated into our device, we are able to obtain a highly accurate estimation about posture and altitude of the subject. By means of such information, we have developed an extremely efficient system for fall detection, reaching 100% of sensitivity in commonly adopted testing protocols. In particular, the algorithm was tested according to three different experimental protocols, where volunteers performed several scenarios, including various types of falls, falls with recovery, and daily living activities frequent in the elderly. Results show that the proper combined use of the four sensors and efficient data fusion algorithms allow to achieve noticeable better performances to those obtained with similar systems proposed in the literature.

An accurate device for real-time altitude estimation using data fusion algorithms

This paper presents an accurate system to estimate the altitude of a rigid body by fusing data from four low-cost sensors such as an accelerometer, a gyroscope, a magnetometer and an altimeter. Usually a MEMS altimeter barometric sensor allows to obtain the altitude signal from measures of atmospheric pressure and temperature but these measures are affected by noise that causes a significant error in the calculated altitude values. In order to get an accurate estimation of the altitude, in this work a complementary filter is used to fuse the raw signal of the altitude obtained from barometer sensor and vertical displacement signal calculated through a data fusion algorithm applied to the signals of the other three sensors. In order to evaluate the performance in human activity monitoring applications, the proposed device has been tested and compared with the system that currently presents the better performance for the same technology according to its experimental protocols. The results show that our device exceeds the performance provided by the currently systems reported in literature.

SVM-based fall detection method for elderly people using Android low-cost smartphones

Nowadays society is moving to a scenery where autonomous elderly live alone in their houses. An automatic remote monitoring system using wearable and ambient sensors is becoming even more important, and is a challenge for the future in WSNs, AAL, and Home Automation areas. Relating to this, one of the most critical events for the safety and the health of the elderly is the fall. Lot of methods, applications, and stand-alone devices have been presented so far. This work proposes a novel method based on the Support Vector Machine technique and addressed to Android low-cost smartphones. Our method starts from data acquired from accelerometer and magnetometer, now available in all the low-end devices, and uses a set of features extracted from a processing of the two signals. After an initial training, the classification of fall events and non-fall events is performed by the Support Vector Machine algorithm. Since we have decided to use the smartphone as monitoring device, the use of other invasive wearable sensors is avoided, and the user have simply to hold the phone on his pocket. Moreover, we can use the cellular network for the eventual sending of notifications and alerts to relatives in case of falls. Actually, our tests show a good performance with a sensitivity of 99.3% and a specificity of 96%.

IPv6 WSN solution for integration and interoperation between smart home and AAL systems

The latest advances in electronic and telecommunication have led to the introduction of intelligent and complex systems: the Wireless Sensor Networks. This technology has become even more important with the advent of the Internet of Things: each node acquires an IPv6 address and can be directly accessed from remote when the switch from IPv4 to IPv6 will take place. Such systems are actually applied in environment monitoring, home automation, industry, and lot of other fields. The Ambient Assisted Living scenery is a perfect field of application for sensor networks based on the IP protocol. The monitoring of elderly people, the automation of home appliances and the assistance to the person can be easily achieved through a network based on IPv6. Furthermore, such a system allows to obtain a maximum interoperability with existent networks, avoiding the need for inconvenient gateways to interface systems with different communication protocols. The presented work describes a complete hardware and software system able to solve the interoperability issue among Smart Home and Ambient Assisted Living. Sub GHz frequency, mesh topology and low power consumption give a competitive advantage to the system against Bluetooth Low Energy or ZigBee technology.

Indoor localization system for AAL over IPv6 WSN

Wireless Sensor Networks are becoming even more a key element in networking and telecommunications especially with the advent of the Internet of Things paradigm, where each single device obtains a unique IPv6 address and is potentially reachable from everywhere through the Internet. Such technologies can be applied in many application fields with great success in terms of optimization of costs and resources, variety of implemented features, level of customization and expandability of each solution. Ambient Assisted Living is definitely one of the most interesting area for WSN and IoT application. In this scenery we propose an applicative example of the use of a IPv6 self configuring WSN with mesh topology. The network is formed by low cost and low power sensor nodes that integrate sub-GHz radio connectivity, belonging to the so-called LLN (Low Power and Lossy Network) scenery. The network stack is fully compatible with the major RFCs about Internet and wireless communications (CSMA, 6LowPAN, uIP, UDP, CoAP, etc.). The case study is a localization system using RSSI feature and does not need additional expensive hardware to be integrated into the nodes. The system proves to be fundamental in indoor environments (houses, clinics, nursing homes) for AAL systems that require localization or tracking of patients and medical equipments. Our tests are performed in extremely complex environment and shown good results localizing targets with an average error of about 2 meters that allows to properly detect the room where targets are located.

An innovative WebRTC solution for e-Health services

Solutions and services for e-Health and telemedicine are constantly spreading and becoming increasingly important in the health area thanks to last innovations in electronics, informatics and telecommunications. This work proposes an innovative service for the e-Health oriented to the maximum ease of use and to the sharing of vital signs. The proposal consists in a tele-counseling service based on the WebRTC technology that allows any person residing remotely from medical staff or hospital to directly interact with them. Our solution provides all the common functions of the WebRTC, such as real-time video and audio streams, instant messaging, and file sharing with the only requirement of a traditional web browser. Beyond that, we implemented the real-time transmission and visualization of vital signs and parameters acquired by biomedical sensors connected to the patients personal device through the RTCDataChannel. Currently our solution involves the installation of a browser extension, but this operation is very simple and may be avoided when WebRTC APIs and browsers will support media streams coming from sensors at the same way as audio and video streams. Our solution demonstrates how web technologies can be applied in the health sector providing very effective services to patients and users which for various reasons have difficulties to travel to hospitals in order to have medical support.

A versatile ankle-mounted fall detection device based on attitude heading systems

In this paper we propose a wireless wearable device for real-time fall detection attached to the ankle user. This device can also be embedded inside the footwear with similar performance and a lower invasiveness of use. It contains a 3-axis accelerometer, a 3-axis gyroscope and a 3-axis magnetometer realizing an Attitude Heading Reference System (AHRS). The AHRS provides the correct 3D orientation through an implemented data fusion algorithm. On sensor board is also implemented the automatic fall detection algorithm handling the orientation data from AHRS and the acceleration data from the triaxial accelerometer. The fall is a critical event that can cause physical and psychological effects particularly among older people. The elderly timely assistance after a fall could prevent serious health care consequences. For this reason the alarms generated by fall detection algorithm are sent to a smartphone via the Bluetooth module integrated into the device. In the smartphone runs a background application that sends sms alert to preset phone numbers or makes prerecorded phone calls after receiving alarms from the sensor node. In order to evaluate the performance of the proposed fall detection system, the developed device has been tested according to an experimental protocol in which volunteers perform simulated falls, simulated falls with recovery and activities of daily living (ADL). Our ankle-mounted devise shows a significant improvement in performance compared to other devices proposed in literature. In fact, the results of the experimental protocol show a sensitivity of 97% and a specificity of 100%.

A Software Tool for the Annotation of Embolic Events in Echo Doppler Audio Signals

The use of precordial Doppler monitoring to prevent decompression sickness (DS) is well known by the scientific community as an important instrument for early diagnosis of DS. However, the timely and correct diagnosis of DS without assistance from diving medical specialists is unreliable. Thus, a common protocol for the manual annotation of echo Doppler signals and a tool for their automated recording and annotation are necessary. We have implemented original software for efficient bubble appearance annotation and proposed a unified annotation protocol. The tool auto-sets the response time of human “bubble examiners,” performs playback of the Doppler file by rendering it independent of the specific audio player, and enables the annotation of individual bubbles or multiple bubbles known as “showers.” The tool provides a report with an optimized data structure and estimates the embolic risk level according to the Extended Spencer Scale. The tool is built in accordance with ISO/IEC 9126 on software quality and has been projected and tested with assistance from the Divers Alert Network (DAN) Europe Foundation, which employs this tool for its diving data acquisition campaigns.