Paola Pierleoni

Computing the free distance of turbo codes and serially concatenated codes with interleavers: algorithms and applications

We present a new algorithm for computing the free distance d/sub free/ of parallel and serially concatenated codes with interleavers, the parameter that dominates the code performance at very high signal-to-noise ratios (SNRs). The knowledge of d/sub free/ allows one to analytically estimate the error floor, which may prevent the use of concatenated codes in applications requiring very low error rates. The algorithm is based on the new notion of constrained subcodes, and permits the computation of large distances for large interleavers without a constraint on the input sequence weight (e.g., up to d/sub free/=40 for a rate-1/3 turbo code with interleaver length N=3568). Applications to practical cases of relevant interest, i.e., (1) the new Consultative Committee for Space Data Systems (CCSDS) standard for deep-space telemetry and (2) the new UMTS/3GPP standard for third-generation personal communications, are presented for the first time. Other related aspects, like a study on the free distance distribution of turbo codes with small/medium interleaver length, and a comparison between parallel and serial concatenation behavior, are also discussed.

A new chaotic algorithm for video encryption

We present a new encryption algorithm for the video signal that, employing suitably arranged chaotic functions, allows to increase the security level while maintaining acceptable processing times. We analyze the performance of the new scheme either though simulation or via practical implementation, thus demonstrating its efficiency, also in comparison with previous proposals.

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.

Coupled-soliton photonic logic gates: practical design procedures

The feasibility of and, or, and ex-or functions based on the interaction of optical solitons is proved by use of a five-layer dielectric structure with a nonlinear core. With the exception of the or logic gate, the design of these devices is rather flexible, offering a wide variety of choices with respect to both the geometrical parameters and the input power levels.

SPINE-HRV: A BSN-Based Toolkit for Heart Rate Variability Analysis in the Time-Domain

The Heart Rate Variability (HRV) is based on the analysis of the R-peak to R-peak intervals (RR-intervals) of the ECG signal in the time and/or frequency domains. Doctors and psychologists are increasingly recognizing the importance of HRV; in fact, a number of studies have demonstrated that patients with anxiety, phobias and post-traumatic stress disorder consistently show lower HRV, even when not exposed to a trauma related prompt. Importantly, this relationship existed independently of age, gender, trait anxiety, cardio-respiratory fitness, heart rate, blood pressure and respiration rate. In this paper, we present a toolkit based on body sensor networks (BSN) for the time-domain HRV analysis, namely SPINE-HRV (Signal Processing In Node Environment-HRV). The SPINE-HRV is composed of a wearable heart activity monitoring system to continuously acquire the RR-intervals, and a processing application developed using the SPINE framework. The developed system consists of a wireless chest band, a wireless wearable sensor node and a base station. The RR-intervals are processed using the SPINE framework at the base station side through a time-domain analysis of HRV. The analysis provides seven common parameters known in medical literature to help cardiologists in the diagnosis related to several heart diseases. In particular, SPINE-HRV is applied for stress detection of people during activities in their everyday life. Experimentations carried out by monitoring subjects in specific activities have shown the effectiveness of SPINE-HRV in detecting stress.

An android-based heart monitoring system for the elderly and for patients with heart disease

The current trend in health monitoring systems is to move from the hospital to portable personal devices. This work shows how consumer devices like heart rate monitors can be used not only for applications in sports, but also for medical research and diagnostic purposes. The goal pursued by our group was to develop a simple, accurate, and inexpensive system that would use a few pieces of data acquired by the heart rate monitor and process them on a smartphone to (i) provide detailed test reports about the users health state; (ii) store report records; (iii) generate emergency calls or SMSs; and (iv) connect to a remote telemedicine portal to relay the data to an online database. The system developed by our team uses sophisticated algorithms to detect stress states, detect and classify arrhythmia events, and calculate energy consumption. It is suitable for use by elderly subjects and by patients with heart disease (e.g., those recovering from myocardial infarction) or neurological conditions such as Parkinsons disease. Easy, immediate, and economical remote health control can therefore be achieved without the need for expensive hospital equipment, using only portable consumer devices.

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.

Interoperability issues among smart home technological frameworks

Population aging may be seen both as a human success story, the triumph of public health, medical advancements and economic development over diseases and injures, and as one of the most challenging phenomena that society faces in this century. Assistive technology in all its possible implementations (from Telemedicine to Ambient Assisted Living, and Ambient Intelligence) represents an emerging answer to the needs of the new generation of older adults whose desire is to live longer with a higher quality of life. Objective of this paper is to present the results of a public financed action for the development and implementation of an “integration platform” for Ambient Assisted Living that includes features of home automation (energy management, safety, comfort, etc.) and introduces “smart objects”, to monitor activities of daily living and detect any abnormal behavior that may represent a danger, or highlight symptoms of some incipient disease.

A real-time system to aid clinical classification and quantification of tremor in Parkinson's disease

The availability of an objective clinical evaluation in the diagnosis and monitoring of parkinsons disease is a primary importance objective in neurology. Furthermore, in many patients next to resting tremor typical of the disease are also found other types of tremor as kinetic and postural tremor so making the diagnosis difficult. The ability to classify the different types of tremor specific for each patient through an examination of the instrumental, non-invasive and very simple and fast is a great tool to aid the clinical diagnosis of the disease. Our system meets the above requirements. It consists of an inertial sensor that allows the acquisition of the quantities of interest, and by a series of algorithms able to provide an objective and quantitative assessment of the type and severity of tremor in patients with Parkinsons disease. The availability of an objective report on the severity of the disorder developed according to a strict correlation with the valuation provided by the UPDRS scale is a good starting point towards the personalization of care as well as being a useful tool in the analysis of the course of the disease.

Comparison of H.264/AVC, H.264 with AIF, and AVS based on different video quality metrics

Video communication has a very important role nowadays. Also very efficient video coding techniques are developed in order to provide high quality video streams using all the available bandwidth. In this work we perform a comparison between three different video codecs: the ITU-T H.264, an improved ITU-T H.264 version including the AIF (Adaptive Interpolation Filter), and the AVS (Audio and Video Coding Standard) that is the Chinese standard video codec. The realized tests involve eight standard video sequences that are coded end decoded using the mentioned standards. Then, for each sequence we evaluate the video quality using four objective metrics: PSNR (Peak Signal-to-Noise Ratio), VQM (Video Quality Metric), SSIM (Structural SIMilarity), and the HSM (HVS - Human Visual System - Similarity Measure). While PSNR and VQM take into account the mathematical features of the video sequences, SSIM and HSM are based on the HVS theory. So it is possible to evaluate also the human eye perceived quality. The realized analysis is related to the relationship between the bitrate and the quality indexes. The conclusions of our analysis can give an evaluation about several codec performances and can be useful for developers to plan and manage their network. Also, taking into account the HSM scores, the AVS has better performance than the ITU-T video codecs.