Long term recording of biomedical signals such as ECG, EMG, respiration and other information (e.g. body motion) can improve diagnosis and potentially monitor the evolution of many widespread diseases. However, long term monitoring requires specific solutions, portable and wearable equipment that should be particularly comfortable for patients. The key-issues of portable biomedical instrumentation are: power consumption, long-term sensor stability, comfortable wearing and wireless connectivity. In this scenario, it would be valuable to realize prototypes using available technologies to assess long-term personal monitoring and foster new ways to provide healthcare services. The aim of this work is to discuss the advantages and the drawbacks in long term monitoring of biopotentials and body movements using textile electrodes embedded in clothes. The textile electrodes were embedded into garments; tiny shirt and short were used to acquire electrocardiographic and electromyographic signals. The garment was equipped with low power electronics for signal acquisition and data wireless transmission via Bluetooth. A small, battery powered, biopotential amplifier and three-axes acceleration body monitor was realized. Patient monitor incorporates a microcontroller, analog-to-digital signal conversion at programmable sampling frequencies. The system was able to acquire and to transmit realtime signals, within 10 m range, to any Bluetooth device (including PDA or cellular phone). The electronics were embedded in the shirt resulting comfortable to wear for patients. Small size MEMS 3-axes accelerometers were also integrated.

The aim of the study is to characterize the local muscles motion in individuals undergoing whole body mechanical stimulation. In this study we aim also to evaluate how subject positioning modifies vibration dumping, altering local mechanical stimulus. Vibrations were delivered to subjects by the use of a vibrating platform, while stimulation frequency was increased linearly from 15 to 60 Hz. Two different subject postures were here analysed. Platform and muscles motion were monitored using tiny MEMS accelerometers; a contra lateral analysis was also presented. Muscle motion analysis revealed typical displacement trajectories: motion components were found not to be purely sinusoidal neither in phase to each other. Results also revealed a mechanical resonant-like behaviour at some muscles, similar to a second-order system response. Resonance frequencies and dumping factors depended on subject and his positioning. Proper mechanical stimulation can maximize muscle spindle solicitation, which may produce a more effective muscle activation.

Monitoring foetal health is important to appropriately plan pregnancy management and delivery. Cardiotocography (CTG) is one of the most employed diagnostic techniques. Because CTG interpretation still lacks of complete reliability, new methods of interpretation and parameters are necessary to further support physicians' decisions. To this aim, indexes related to variability of foetal heart rate (FHRV) are particularly studied. Frequency components of FHRV and their modifications can be analysed by applying a time-frequency approach, which allows for a distinct understanding of the spectral components related to foetal reactions to internal and external stimuli and their change over time. Being uterine contractions (UC) strong stimuli for the foetus and his autonomic nervous system (ANS), it is worth exploring the FHRV response to UC. This study analysed modifications of FHRV frequency characteristics with respect to 108 UC (relative to 35 healthy foetuses). Results showed a statistically significant (t-test, p < 0.01) power increase of the FHRV in both LF and HF bands in correspondence of the contractions. Moreover, we observed a shift to higher values of the maximum frequency contained in the signal corresponding to the power increase. Such modifications of the FHRV power spectrum can be a sign of ANS reaction and therefore represent additional, objective information about foetal reactivity and health during labour.

This study extends a previous research concerning intervertebral motion registration by means of 2D dynamic fluoroscopy to obtain a more comprehensive 3D description of vertebral kinematics. The problem of estimating the 3D rigid pose of a CT volume of a vertebra from its 2D X-ray fluoroscopy projection is addressed. 2D-3D registration is obtained maximising a measure of similarity between Digitally Reconstructed Radiographs (obtained from the CT volume) and real fluoroscopic projection. X-ray energy correction was performed. To assess the method a calibration model was realised a sheep dry vertebra was rigidly fixed to a frame of reference including metallic markers. Accurate measurement of 3D orientation was obtained via single-camera calibration of the markers and held as true 3D vertebra position; then, vertebra 3D pose was estimated and results compared. Error analysis revealed accuracy of the order of 0.1 degree for the rotation angles of about 1 mm for displacements parallel to the fluoroscopic plane, and of order of 10 mm for the orthogonal displacement.

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Analysis of dynamic videofluoroscopic can provide spine kinematic data with an acceptable low X-ray dose. Estimation of the kinematics relies on accurate recognition of vertebrae positions and rotations on each radiological frame. In previous works we presented a procedure for automatic tracking of vertebra motion by smoothed gradient operators and template matching in fluoroscopic image sequences. A limitation to the accurate estimation of the kinematics by automatic tracking of vertebrae motion, independently by the specific methodology employed (e.g. manual marking, corner or edge automatic detection, etc.), is mainly due to noise: low-dose X-ray image sequences exhibit severe signal-dependent noise that should be reduced, while preserving anatomical edges and structures. Noise in low-dose X-ray images originates from various sources, however quantum noise is by far the more dominant noise in low-dose X-ray images and other sources can be neglected. Signal degraded by quantum noise is commonly modeled by a Poisson distribution, but it is possible to approximate it as additive zero-mean Gaussian noise with signal-dependent variance. In this work we propose a digital spatial filter for reducing noise in low-dose X-ray images. The proposed filter is based on averaging of only similar pixels (whose grey level is contained within ±3σ) instead of spatial averaging of all neighbouring pixels. The effectiveness of the filter performance was evaluated by fluoroscopic image sequence processing, comparing the results of the automatic vertebra tracking on filtered and unfiltered images