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Purpose: 3D visualization is an important part of learning anatomy with cadavers generally used to effectuate this. However, high cost, ethical considerations, and limited accessibility can often limit the suitability of cadavers as teaching tools. Anatomical 3D printed models offer an alternative tool for teaching gross anatomy due to their low cost and accessibility. This study aims to investigate if combing gamification with 3D printed models can enhance the learning experience and be effective for teaching anatomy. Methods: 3D printed models of the bones of the foot and ankle were generated, and 267 first-year medical students from 2 consecutive cohorts worked in groups to put it together as a puzzle. Participants completed a questionnaire regarding perceptions of 3D models and their knowledge of foot anatomy, before and after the session and were asked to provide comments. Results: Analysis of the responses showed a significant increase in the confidence of the learners in their anatomy knowledge and an increased appreciation of the role that 3D models have in enhancing the learning experience. After the session, there were many comments saying how enjoyable and engaging 3D models were. Conclusion: Through the puzzle element of the session, the students were challenged mentally to work out the anatomical features of the foot and ankle. The combined elements of the puzzle and the features of the 3D model assembly made the activity fun and conducive to active learning. The possibility of having fun was not something the students had considered before the session. [ABSTRACT FROM AUTHOR]

Introduction: There is accumulating evidence that many pathological conditions affecting human balance are consequence of postural control (PC) failure or overstimulation such as in motion sickness. Our research shows the potential of using the response to a complex postural control task to assess patients with early-stage Parkinson's Disease (PD). Methods: We developed a unique measurement model, where the PC task is triggered by a moving platform in a virtual reality environment while simultaneously recording EEG, EMG and CoP signals. This novel paradigm of assessment is called BioVRSea. We studied the interplay between biosignals and their differences in healthy subjects and with early-stage PD. Results: Despite the limited number of subjects (29 healthy and nine PD) the results of our work show significant differences in several biosignals features, demonstrating that the combined output of posturography, muscle activation and cortical response is capable of distinguishing healthy from pathological. Discussion: The differences measured following the end of the platform movement are remarkable, as the induced sway is different between the two groups and triggers statistically relevant cortical activities in α and θ bands. This is a first important step to develop a multi-metric signature able to quantify PC and distinguish healthy from pathological response. [ABSTRACT FROM AUTHOR]

Research on human posture and balance control has grown in recent years, leading to continued advances in their understanding. The ability to maintain balance is attributed to the interplay of the visual, vestibular, and somatosensory systems, although an important role is also played by the auditory system. The lack or deficit in any of these systems leads to a reduced stability that may be counterbalanced by the integration of all the remaining sensory information. Auditory and vibratory stimulation have been found to be useful to enhance balance alongside daily activities either in healthy or pathological subjects; nevertheless, while widely investigated, the literature relating to these approaches is still fragmented. This review aims at addressing this by collecting, organising, and discussing all the literature to date on the effects of the various acoustic and vibratory stimulation techniques available on static upright posture in healthy subjects. In addition, this review intends to provide a solid and comprehensive starting point for all the researchers interested in these research areas. A systematic search of the literature was performed and a total of 33 articles (24 on vibratory stimulation and 9 on acoustic stimulation) were included in our analysis. For all articles, several elements were highlighted including: the study sample, the characteristics of the stimulations, the recording instruments, the experimental protocols, and outcomes. Overall, both stimulations analysed were found to have a positive effect on balance but more research is needed to align those alternative approaches to the traditional ones. [ABSTRACT FROM AUTHOR]

Efficient postural control results from an effective interplay between sensory feedbacks integration and muscle modulation and can be affected by ageing and neuromuscular injuries. With this study, we investigated the effect of whole-body vibratory stimulation on postural control strategies employed to maintain an upright posture. We explored both physiological and posturography metrics, through corticomuscular and intramuscular coherence, and muscle networks analyses. The stimulation disrupts balance in the short term, but leads to a greater contribution of cortical activity, necessary to modulate muscle activation via the formation of (new) synergies. We also observed a reconfiguration of muscle recruitment patterns that returned to pre-stimulation levels after few minutes, accompanied by a slight improvement of balance in the anterior–posterior direction. Our results suggest that, in the context of postural control, appropriate mechanical stimulation is capable of triggering a recalibration of the sensorimotor set and might offer new perspectives for motor re-education. [ABSTRACT FROM AUTHOR]

The aim of this study is to characterise the transient mechanical response and the neuromuscular activation of lower limb muscles in subjects undergoing Whole Body Vibration (WBV) at different frequencies while holding two static postures, with focus on muscles involved in shaping postural responses. Twenty-five participants underwent WBV at 15, 20, 25 and 30 Hz while in hack squat or on fore feet. Surface electromyography and soft tissue accelerations were collected from Gastrocnemius Lateralis (GL), Soleus (SOL) and Tibialis Anterior (TA) muscles. Estimated displacement at muscle bellies revealed a pattern never highlighted before that differed across frequencies and postures (p < 0.001). After stimulation starts, muscle oscillation peaks, drops and further stabilises, suggesting the occurrence of a neuromuscular activation to reduce the vibration-induced oscillation. The oscillation attenuation at the SOL muscle correlated with its increased activation (rho = 0.29, p < 0.001). Furthermore, only specific WBV settings led to a significant increase in muscle contraction: WBV-induced activation of SOL and GL was maximal in fore-feet (p < 0.05) and in response to higher frequencies (30 Hz vs 15 Hz, p < 0.001). The analysis of the mechanical dynamics of lower leg muscles highlights a resonant response to WBVs, that for the SOL correlates to the increased muscle activation. Despite differing across frequencies and postures, this resonant behaviour seems to discourage the use of dynamic exercises on vibrating platforms. As for the most efficient WBV combination, calf muscle response to WBVs is maximised if those muscles are already pre-contracted and the stimulation frequencies are in the 25–30 Hz range. [ABSTRACT FROM AUTHOR]

Postural control is a complex feedback system that relies on vast array of sensory inputs in order to maintain a stable upright stance. The brain cortex plays a crucial role in the processing of this information and in the elaboration of a successful adaptive strategy to external stimulation preventing loss of balance and falls. In the present work, the participants postural control system was challenged by disrupting the upright stance via a mechanical skeletal muscle vibration applied to the calves. The EEG source connectivity method was used to investigate the cortical response to the external stimulation and highlight the brain network primarily involved in high-level coordination of the postural control system. The cortical network reconfiguration was assessed during two experimental conditions of eyes open and eyes closed and the network flexibility (i.e. its dynamic reconfiguration over time) was correlated with the sample entropy of the stabilogram sway. The results highlight two different cortical strategies in the alpha band: the predominance of frontal lobe connections during open eyes and the strengthening of temporal-parietal network connections in the absence of visual cues. Furthermore, a high correlation emerges between the flexibility in the regions surrounding the right temporo-parietal junction and the sample entropy of the CoP sway, suggesting their centrality in the postural control system. These results open the possibility to employ network-based flexibility metrics as markers of a healthy postural control system, with implications in the diagnosis and treatment of postural impairing diseases. [ABSTRACT FROM AUTHOR]

Background: Low-dose X-ray images have become increasingly popular in the last decades, due to the need to guarantee the lowest reasonable patient's exposure. Dose reduction causes a substantial increase of quantum noise, which needs to be suitably suppressed. In particular, real-time denoising is required to support common interventional fluoroscopy procedures. The knowledge of noise statistics provides precious information that helps to improve denoising performances, thus making noise estimation a crucial task for effective denoising strategies. Noise statistics depend on different factors, but are mainly influenced by the X-ray tube settings, which may vary even within the same procedure. This complicates real-time denoising, because noise estimation should be repeated after any changes in tube settings, which would be hardly feasible in practice. This work investigates the feasibility of an a priori characterization of noise for a single fluoroscopic device, which would obviate the need for inferring noise statics prior to each new images acquisition. The noise estimation algorithm used in this study was tested in silico to assess its accuracy and reliability. Then, real sequences were acquired by imaging two different X-ray phantoms via a commercial fluoroscopic device at various X-ray tube settings. Finally, noise estimation was performed to assess the matching of noise statistics inferred from two different sequences, acquired independently in the same operating conditions.Results: The noise estimation algorithm proved capable of retrieving noise statistics, regardless of the particular imaged scene, also achieving good results even by using only 10 frames (mean percentage error lower than 2%). The tests performed on the real fluoroscopic sequences confirmed that the estimated noise statistics are independent of the particular informational content of the scene from which they have been inferred, as they turned out to be consistent in sequences of the two different phantoms acquired independently with the same X-ray tube settings.Conclusions: The encouraging results suggest that an a priori characterization of noise for a single fluoroscopic device is feasible and could improve the actual implementation of real-time denoising strategies that take advantage of noise statistics to improve the trade-off between noise reduction and details preservation. [ABSTRACT FROM AUTHOR]

The objective of the present work is to measure postural kinematics and power spectral variation from HD-EEG to assess changes in cortical activity during adaptation and habituation to postural perturbation. To evoke proprioceptive postural perturbation, vibratory stimulation at 85 Hz was applied to the calf muscles of 33 subjects over four 75-second stimulation periods. Stimulation was performed according to a pseudorandom binary sequence. Vibratory impulses were synchronized to high-density electroencephalography (HD-EEG, 256 channels). Changes in absolute spectral power (ASP) were analyzed over four frequency bands ($ {\Delta }$ : 0.5–3.5 Hz; $ {\theta }$ : 3.5–7.5 Hz; $ {\alpha }$ : 7.5–12.5 Hz; $ {\beta }$ : 12.5–30 Hz). A force platform recorded torque actuated by the feet, and normalized sway path length (SPL) was computed as a construct for postural performance during each period. SPL values indicated improvement in postural performance over the trial periods. Significant variation in absolute power values (ASP) was found in assessing postural adaptation: an increase in $ {\theta }$ band ASP in the frontal-central region for closed-eyes trials, an increase in $ {\theta }$ and $ {\beta }$ band ASP in the parietal region for open-eyes trials. In habituation, no significant variations in ASP were observed during closed-eyes trials, whereas an increase in $ {\theta }$ , $ {\alpha }$ , and $ {\beta }$ band ASP was observed with open eyes. Furthermore, open-eyed trials generally yielded a greater number of significant ASP differences across all bands during both adaptation and habituation, suggesting that following cortical activity during postural perturbation may be up-regulated with the availability of visual feedback. These results altogether provide deeper insight into pathological postural control failure by exploring the dynamic changes in both cortical activity and postural kinematics during adaptation and habituation to proprioceptive postural perturbation. [ABSTRACT FROM AUTHOR]

Human machine interfaces (HMIs) are employed in a broad range of applications, spanning from assistive devices for disability to remote manipulation and gaming controllers. In this study, a new piezoresistive sensors array armband is proposed for hand gesture recognition. The armband encloses only three sensors targeting specific forearm muscles, with the aim to discriminate eight hand movements. Each sensor is made by a force-sensitive resistor (FSR) with a dedicated mechanical coupler and is designed to sense muscle swelling during contraction. The armband is designed to be easily wearable and adjustable for any user and was tested on 10 volunteers. Hand gestures are classified by means of different machine learning algorithms, and classification performances are assessed applying both, the 10-fold and leave-one-out cross-validations. A linear support vector machine provided 96% mean accuracy across all participants. Ultimately, this classifier was implemented on an Arduino platform and allowed successful control for videogames in real-time. The low power consumption together with the high level of accuracy suggests the potential of this device for exergames commonly employed for neuromotor rehabilitation. The reduced number of sensors makes this HMI also suitable for hand-prosthesis control. [ABSTRACT FROM AUTHOR]

Continuous monitoring of pacemaker activity can provide valuable information to improve patients’ follow-up. Concise information is stored in some types of pacemakers, whereas ECG can provide more detailed information, but requires electrodes and cannot be used for continuous monitoring. This study highlights the possibility of a continuous monitoring of pacemaker pulses by sensing magnetic field variations due to the current pulses. This can be achieved by means of a sensor coil positioned near the patient’s thorax without any need for physical contact. A simplified model of coil response to pacemaker pulses is presented in this paper, along with circuits suitable for pulse detection. In vitro tests were carried out using real pacemakers immersed in saline solution; experimental data were used to assess the accuracy of the model and to evaluate the sensor performance. It was found that the coil signal amplitude decreases with increasing distance from the pacemaker lead wire. The sensor was able to easily perform pacemaker spike detection up to a distance of 12 cm from the pacemaker leads. The stimulation rate can be measured in real time with high accuracy. Since any electromagnetic pulse triggers the same coil response, EMI may corrupt sensor measurements and thus should be discriminated. [ABSTRACT FROM AUTHOR]

This study provides a definitive analysis of the spectrum of a motor unit action potential train (MUAPT) elicited by mechanical vibratory stimulation via a detailed and concise mathematical formulation. Experimental studies demonstrated that MUAPs are not exactly synchronized with the vibratory stimulus but show a variable latency jitter, whose effects have not been investigated yet. Synchronized action potential train was represented as a quasi-periodic sequence of a given MU waveform. The latency jitter of action potentials was modeled as a Gaussian stochastic process, in accordance to the previous experimental studies. A mathematical expression for power spectrum of a synchronized MUAPT has been derived. The spectrum comprises a significant continuous component and discrete components at the vibratory frequency and its harmonics. Their relevance is correlated to the level of synchronization: the weaker the synchronization the more relevant is the continuous spectrum. Electromyography (EMG) rectification enhances the discrete components. The derived equations have general validity and well describe the power spectrum of actual EMG recordings during vibratory stimulation. Results are obtained by appropriately setting the level of synchronization and vibration frequency. This paper definitively clarifies the nature of changes in spectrum of raw EMG recordings from muscles undergoing vibratory stimulation. Results confirm the need of motion artifact filtering for raw EMG recordings during stimulation and strongly suggest to avoid EMG rectification that significantly alters the spectrum characteristics. [ABSTRACT FROM AUTHOR]

Whole body vibration treatment is a non-pharmacological intervention intended to stimulate muscular response and increase bone mineral density, particularly for postmenopausal women. The literature related to this topic is controversial, heterogeneous, and unclear despite the prospect of a major clinical effect.The aim of this study was to identify and systematically review the literature to assess the effect of whole body vibration treatments on bone mineral density (BMD) in postmenopausal women with a specific focus on the experimental factors that influence the stimulus. Nine studies fulfilled the inclusion criteria, including 527 postmenopausal women and different vibration delivery designs. Cumulative dose, amplitudes and frequency of treatments as well as subject posture during treatment vary widely among studies. Some of the studies included an associated exercise training regime. Both randomized and controlled clinical trials were included. Whole body vibration was shown to produce significant BMD improvements on the hip and spine when compared to no intervention. Conversely, treatment associated with exercise training resulted in negligible outcomes when compared to exercise training or to placebo. Moreover, side-alternating platforms were more effective in improving BMD values than synchronous platforms and mechanical oscillations of magnitude higher than 3 g and/or frequency lower than 25 Hz were also found to be effective. Treatments with a cumulative dose over 1000 minutes in the follow-up period were correlated to positive outcomes.Our conclusion is that whole body vibration treatments in elderly women can reduce BMD decline.However, many factors (e.g., amplitude, frequency and subject posture) affect the capacity of the vibrations to propagate to the target site; the adequate level of stimulation required to produce these effects has not yet been defined. Further biomechanical analyses to predict the propagation of the vibration waves along the body and assess the stimulation levels are required. [ABSTRACT FROM AUTHOR]

Background: During last decade the use of ECG recordings in biometric recognition studies has increased. ECG characteristics made it suitable for subject identification: it is unique, present in all living individuals, and hard to forge. However, in spite of the great number of approaches found in literature, no agreement exists on the most appropriate methodology. This study aimed at providing a survey of the techniques used so far in ECG-based human identification. Specifically, a pattern recognition perspective is here proposed providing a unifying framework to appreciate previous studies and, hopefully, guide future research. Methods: We searched for papers on the subject from the earliest available date using relevant electronic databases (Medline, IEEEXplore, Scopus, and Web of Knowledge). The following terms were used in different combinations: electrocardiogram, ECG, human identification, biometric, authentication and individual variability. The electronic sources were last searched on 1st March 2015. In our selection we included published research on peer-reviewed journals, books chapters and conferences proceedings. The search was performed for English language documents. Results: 100 pertinent papers were found. Number of subjects involved in the journal studies ranges from 10 to 502, age from 16 to 86, male and female subjects are generally present. Number of analysed leads varies as well as the recording conditions. Identification performance differs widely as well as verification rate. Many studies refer to publicly available databases (Physionet ECG databases repository) while others rely on proprietary recordings making difficult them to compare. As a measure of overall accuracy we computed a weighted average of the identification rate and equal error rate in authentication scenarios. Identification rate resulted equal to 94.95 % while the equal error rate equal to 0.92 %. Conclusions: Biometric recognition is a mature field of research. Nevertheless, the use of physiological signals features, such as the ECG traits, needs further improvements. ECG features have the potential to be used in daily activities such as access control and patient handling as well as in wearable electronics applications. However, some barriers still limit its growth. Further analysis should be addressed on the use of single lead recordings and the study of features which are not dependent on the recording sites (e.g. fingers, hand palms). Moreover, it is expected that new techniques will be developed using fiducials and non-fiducial based features in order to catch the best of both approaches. ECG recognition in pathological subjects is also worth of additional investigations. [ABSTRACT FROM AUTHOR]

Background: During last decade the use of ECG recordings in biometric recognition studies has increased. ECG characteristics made it suitable for subject identification: it is unique, present in all living individuals, and hard to forge. However, in spite of the great number of approaches found in literature, no agreement exists on the most appropriate methodology. This study aimed at providing a survey of the techniques used so far in ECG-based human identification. Specifically, a pattern recognition perspective is here proposed providing a unifying framework to appreciate previous studies and, hopefully, guide future research. Methods: We searched for papers on the subject from the earliest available date using relevant electronic databases (Medline, IEEEXplore, Scopus, and Web of Knowledge). The following terms were used in different combinations: electrocardiogram, ECG, human identification, biometric, authentication and individual variability. The electronic sources were last searched on 1st March 2015. In our selection we included published research on peer-reviewed journals, books chapters and conferences proceedings. The search was performed for English language documents. Results: 100 pertinent papers were found. Number of subjects involved in the journal studies ranges from 10 to 502, age from 16 to 86, male and female subjects are generally present. Number of analysed leads varies as well as the recording conditions. Identification performance differs widely as well as verification rate. Many studies refer to publicly available databases (Physionet ECG databases repository) while others rely on proprietary recordings making difficult them to compare. As a measure of overall accuracy we computed a weighted average of the identification rate and equal error rate in authentication scenarios. Identification rate resulted equal to 94.95 % while the equal error rate equal to 0.92 %. Conclusions: Biometric recognition is a mature field of research. Nevertheless, the use of physiological signals features, such as the ECG traits, needs further improvements. ECG features have the potential to be used in daily activities such as access control and patient handling as well as in wearable electronics applications. However, some barriers still limit its growth. Further analysis should be addressed on the use of single lead recordings and the study of features which are not dependent on the recording sites (e.g. fingers, hand palms). Moreover, it is expected that new techniques will be developed using fiducials and non-fiducial based features in order to catch the best of both approaches. ECG recognition in pathological subjects is also worth of additional investigations. [ABSTRACT FROM AUTHOR]

Background: Electrosurgery units are widely employed in modern surgery. Advances in technology have enhanced the safety of these devices, nevertheless, accidental burns are still regularly reported. This study focuses on possible causes of sacral burns as complication of the use of electrosurgery. Burns are caused by local densifications of the current, but the actual pathway of current within patient's body is unknown. Numerical electromagnetic analysis can help in understanding the issue.Methods: To this aim, an accurate heterogeneous model of human body (including seventy-seven different tissues), electrosurgery electrodes, operating table and mattress was build to resemble a typical surgery condition. The patient lays supine on the mattress with the active electrode placed onto the thorax and the return electrode on his back. Common operating frequencies of electrosurgery units were considered. Finite Difference Time Domain electromagnetic analysis was carried out to compute the spatial distribution of current density within the patient's body. A differential analysis by changing the electrical properties of the operating table from a conductor to an insulator was also performed.Results: Results revealed that distributed capacitive coupling between patient body and the conductive operating table offers an alternative path to the electrosurgery current. The patient's anatomy, the positioning and the different electromagnetic properties of tissues promote a densification of the current at the head and sacral region. In particular, high values of current density were located behind the sacral bone and beneath the skin. This did not occur in the case of non-conductive operating table.Conclusion: Results of the simulation highlight the role played from capacitive couplings between the return electrode and the conductive operating table. The concentration of current density may result in an undesired rise in temperature, originating burns in body region far from the electrodes. This outcome is concordant with the type of surgery-related sacral burns reported in literature. Such burns cannot be immediately detected after surgery, but appear later and can be confused with bedsores. In addition, the dosimetric analysis suggests that reducing the capacity coupling between the return electrode and the operating table can decrease or avoid this problem. [ABSTRACT FROM AUTHOR]

Accurate measurement of intervertebral kinematics of the cervical spine can support the diagnosis of widespread diseases related to neck pain, such as chronic whiplash dysfunction, arthritis, and segmental degeneration.The natural inaccessibility of the spine, its complex anatomy, and the small range of motion only permit concise measurement in vivo. Low dose X-ray fluoroscopy allows time-continuous screening of cervical spine during patient's spontaneous motion. To obtain accurate motion measurements, each vertebra was tracked by means of image processing along a sequence of radiographic images. To obtain a time-continuous representation of motion and to reduce noise in the experimental data, smoothing spline interpolation was used. Estimation of intervertebral motion for cervical segments was obtained by processing patient's fluoroscopic sequence; intervertebral angle and displacement and the instantaneous centre of rotation were computed. The RMS value of fitting errors resulted in about 0.2 degree for rotation and 0.2 mm for displacements. [ABSTRACT FROM AUTHOR]

This paper presents forcecardiography (FCG), a novel technique to measure local, cardiac-induced vibrations onto the chest wall. Since the 19th century, several techniques have been proposed to detect the mechanical vibrations caused by cardiovascular activity, the great part of which was abandoned due to the cumbersome instrumentation involved. The recent availability of unobtrusive sensors rejuvenated the research field with the most currently established technique being seismocardiography (SCG). SCG is performed by placing accelerometers onto the subject's chest and provides information on major events of the cardiac cycle. The proposed FCG measures the cardiac-induced vibrations via force sensors placed onto the subject's chest and provides signals with a richer informational content as compared to SCG. The two techniques were compared by analysing simultaneous recordings acquired by means of a force sensor, an accelerometer and an electrocardiograph (ECG). The force sensor and the accelerometer were rigidly fixed to each other and fastened onto the xiphoid process with a belt. The high-frequency (HF) components of FCG and SCG were highly comparable (r > 0.95) although lagged. The lag was estimated by cross-correlation and resulted in about tens of milliseconds. An additional, large, low-frequency (LF) component, associated with ventricular volume variations, was observed in FCG, while not being visible in SCG. The encouraging results of this feasibility study suggest that FCG is not only able to acquire similar information as SCG, but it also provides additional information on ventricular contraction. Further analyses are foreseen to confirm the advantages of FCG as a technique to improve the scope and significance of pervasive cardiac monitoring. [ABSTRACT FROM AUTHOR]

Measurement of muscle contraction is mainly achieved through electromyography (EMG) and is an area of interest for many biomedical applications, including prosthesis control and human machine interface. However, EMG has some drawbacks, and there are also alternative methods for measuring muscle activity, such as by monitoring the mechanical variations that occur during contraction. In this study, a new, simple, non-invasive sensor based on a force-sensitive resistor (FSR) which is able to measure muscle contraction is presented. The sensor, applied on the skin through a rigid dome, senses the mechanical force exerted by the underlying contracting muscles. Although FSR creep causes output drift, it was found that appropriate FSR conditioning reduces the drift by fixing the voltage across the FSR and provides voltage output proportional to force. In addition to the larger contraction signal, the sensor was able to detect the mechanomyogram (MMG), i.e., the little vibrations which occur during muscle contraction. The frequency response of the FSR sensor was found to be large enough to correctly measure the MMG. Simultaneous recordings from flexor carpi ulnaris showed a high correlation (Pearson’s r > 0.9) between the FSR output and the EMG linear envelope. Preliminary validation tests on healthy subjects showed the ability of the FSR sensor, used instead of the EMG, to proportionally control a hand prosthesis, achieving comparable performances. [ABSTRACT FROM AUTHOR]

Background: During last decade the use of ECG recordings in biometric recognition studies has increased. ECG characteristics made it suitable for subject identification: it is unique, present in all living individuals, and hard to forge. However, in spite of the great number of approaches found in literature, no agreement exists on the most appropriate methodology. This study aimed at providing a survey of the techniques used so far in ECG-based human identification. Specifically, a pattern recognition perspective is here proposed providing a unifying framework to appreciate previous studies and, hopefully, guide future research.Methods: We searched for papers on the subject from the earliest available date using relevant electronic databases (Medline, IEEEXplore, Scopus, and Web of Knowledge). The following terms were used in different combinations: electrocardiogram, ECG, human identification, biometric, authentication and individual variability. The electronic sources were last searched on 1st March 2015. In our selection we included published research on peer-reviewed journals, books chapters and conferences proceedings. The search was performed for English language documents.Results: 100 pertinent papers were found. Number of subjects involved in the journal studies ranges from 10 to 502, age from 16 to 86, male and female subjects are generally present. Number of analysed leads varies as well as the recording conditions. Identification performance differs widely as well as verification rate. Many studies refer to publicly available databases (Physionet ECG databases repository) while others rely on proprietary recordings making difficult them to compare. As a measure of overall accuracy we computed a weighted average of the identification rate and equal error rate in authentication scenarios. Identification rate resulted equal to 94.95 % while the equal error rate equal to 0.92 %.Conclusions: Biometric recognition is a mature field of research. Nevertheless, the use of physiological signals features, such as the ECG traits, needs further improvements. ECG features have the potential to be used in daily activities such as access control and patient handling as well as in wearable electronics applications. However, some barriers still limit its growth. Further analysis should be addressed on the use of single lead recordings and the study of features which are not dependent on the recording sites (e.g. fingers, hand palms). Moreover, it is expected that new techniques will be developed using fiducials and non-fiducial based features in order to catch the best of both approaches. ECG recognition in pathological subjects is also worth of additional investigations. [ABSTRACT FROM AUTHOR]