L. Burattini

Evaluation of gender-related differences in co-contraction activity of shank muscles during gait

This study aims to investigate the possible differences between genders in co-contractions of tibialis anterior (TA) and gastrocnemius lateralis (GL), during walking at self-selected speed. To this purpose, the statistical gait analysis (SGA) was performed on seven female (F-group) and seven male (M-group) adults. SGA is a recently developed methodology for the characterization of gait, by averaging spatiotemporal and electromyographic parameters over hundreds of strides per subject. Co-contractions were assessed as the overlapping periods between TA and GL activity. Results showed that four co-contraction intervals are present during gait cycle in both groups. No relevant differences between genders were detected in onset-offset time instants of co-activations or in their temporal length. On the contrary, significant differences were observed in the number of strides where each co-contraction happens (i.e. the occurrence frequency). All the four co-contraction intervals result significantly (p<;0.05) more recurrent in females compared to males. This outcome suggests a larger presence of co-contraction activity in females walking, related to a female tendency for a more complex muscular strategy during gait. These findings could be useful to better understand gender differences in walking mechanisms and to develop separated normal walking reference frames for males and females.

Influence of gender on the myoelectric signal of shank muscles

The surface electromyographic (sEMG) signal is commonly utilized as principal input information to the controller of robotic systems, such as exoskeleton robots. It has been shown that sEMG signals could vary from subject to subject, and that gender is one of the factors influencing this variation. Thus, the goal of this study is to detect possible gender-related differences in the EMG activity of the two main ankle-flexor muscles (tibialis anterior, TA and gastrocnemius lateralis, GL) during gait at comfortable speed and cadence. The statistical analysis of surface EMG signals, performed in seven male (M-group) and seven female (F-group) age-matched adults, showed clear gender-related differences in the behavior of TA and GL. The estimation of the different activation modalities, indeed, permitted to detect that F-group choose a walking modality with a more elevated number of activations during gait cycle, compared to M-group. This suggests a propensity of females for a more complex recruitment of the muscles during gait. The novel information on gender-related differences provided here suggest considering a separate approach for males and females, in providing electromyographic signals as input information to the controller of exoskeleton robot.

The segmented-beat modulation method for ECG estimation.

Electrocardiographic (ECG) tracings corrupted by noise with frequency components in the ECG frequency band, may result useless unless appropriately processed. The estimation of the clean ECG from such recordings, however, is quite challenging; being linear filtering inappropriate. In the common situations in which the R peaks are detectable, template-based techniques have been proposed to estimate the ECG by a template-beat concatenation. However, such techniques have the major limit of not being able to reproduce physiological heart-rate and morphological variability. Thus, the aim of the present study was to propose the segmented-beat modulation method (SBMM) as the technique that overcomes such limit. The SBMM is an improved template-based technique that provides good-quality estimations of ECG tracings characterized by some heart-rate and morphological variability. It segments the template ECG beat into QRS and TUP segments and then, before concatenation, it applies a modulation/demodulation process to the TUP-segment so that the estimated-beat duration and morphology adjust to those of the corresponding original-beat. To test its performance, the SBMM was applied to 19 ECG tracings from normal subjects. There were no errors in estimating the R peak location, and the errors in the QRS and TUP segments were low (≤65 μV and ≤30 μV, respectively), with the former ones being significantly higher than the latter ones. Eventually, TUP errors tended to increase with increasing heart-rate variability (correlation coefficient: 0.59, P<;10-2). In conclusion, the new SBMM proved to be a useful tool for providing good-quality ECG estimations of tracings characterized by heart-rate and morphological variability.

Statistical baseline assessment in cardiotocography

Cardiotocography (CTG) is the most common non-invasive diagnostic technique to evaluate fetal well-being. It consists in the recording of fetal heart rate (FHR; bpm) and maternal uterine contractions. Among the main parameters characterizing FHR, baseline (BL) is fundamental to determine fetal hypoxia and distress. In computerized applications, BL is typically computed as mean FHR±ΔFHR, with ΔFHR=8 bpm or ΔFHR=10 bpm, both values being experimentally fixed. In this context, the present work aims: to propose a statistical procedure for ΔFHR assessment; to quantitatively determine ΔFHR value by applying such procedure to clinical data; and to compare the statistically-determined ΔFHR value against the experimentally-determined ΔFHR values. To these aims, the 552 recordings of the “CTU-UHB intrapartum CTG database” from Physionet were submitted to an automatic procedure, which consisted in a FHR preprocessing phase and a statistical BL assessment. During preprocessing, FHR time series were divided into 20-min sliding windows, in which missing data were removed by linear interpolation. Only windows with a correction rate lower than 10% were further processed for BL assessment, according to which ΔFHR was computed as FHR standard deviation. Total number of accepted windows was 1192 (38.5%) over 383 recordings (69.4%) with at least an accepted window. Statistically-determined ΔFHR value was 9.7 bpm. Such value was statistically different from 8 bpm (P<10−19) but not from 10 bpm (P=0.16). Thus, ΔFHR=10 bpm is preferable over 8 bpm because both experimentally and statistically validated.

A New Segmented-Beat Modulation Algorithm for Maternal ECG Estimation from Abdominal Recordings

The noninvasive fetal electrocardiogram (fECG) provides precious information about the physiological fetus state. It is extracted from abdominal recordings, obtained positioning surface electrodes on the maternal abdomen, by subtraction of the maternal ECG (mECG), often roughly estimated by simply concatenating a maternal-beat template. Aim of the present study is to propose a new algorithm for the mECG estimation based on a segmented-beat modulation method (SBMM) that adjusts the template length to the maternal physiological heart-rate variability (HRV) and reduces the level of noise. According to the SBMM, each maternal cardiac cycle (CC) is segmented into two segments, QRS and TUP, respectively independent and proportional to preceding RR interval. The estimated mECG is the concatenation of the template-beat, obtained as the median of the maternal beat after modulation and demodulation of TUP segment. The algorithm was applied to two (ARec1 and ARec2) 4-channel abdominal recordings obtained from pregnant women. ARec1 and ARec2 were both 60 s long and characterized by similar heart rate (HR: 80 bpm and 82 bpm) but different HRV (42 ms vs. 139 ms). Results indicate that the error in the mECG estimation is always small (<2.5 µV) but increases with HRV (ARec1: 0.87–1.65 µV; ARec2: 1.98–2.37 µV). In conclusion, the proposed algorithm based on the SBMM allows a clean mECG estimation from abdominal recordings thanks to a modulation procedure introduced to track physiological variation in the maternal heart rhythm.

A goniometer-based method for the assessment of gait parameters

Basic prerequisites for gait analysis are the assessment of spatio-temporal gait parameters and the analysis of movements within subsequent stride cycles. The aim of the present study is to propose a new method to assess spatio-temporal gait parameters using only 1-degree-of-freedom electrogoniometers positioned on hip and knee joints. The model validation is performed comparing the model results with those automatically obtained from another gait analysis system: GAITRite. The results underline the model reliability and show that the model could be a valid alternative to the traditional methods that use foot switches, ground reaction forces or accelerometers. These results show that essential spatio-temporal gait parameters can be determined during overground walking using only two 1-dof electrogoniometers. The method is easy-to-use and does not interfere with regular walking patterns.

Noninvasive Fetal Electrocardiography Part II: Segmented-Beat Modulation Method for Signal Denoising

Background: Fetal well-being evaluation may be accomplished by monitoring cardiac activity through fetal electrocardiography. Direct fetal electrocardiography (acquired through scalp electrodes) is the gold standard but its invasiveness limits its clinical applicability. Instead, clinical use of indirect fetal electrocardiography (acquired through abdominal electrodes) is limited by its poor signal quality. Objective: Aim of this study was to evaluate the suitability of the Segmented-Beat Modulation Method to denoise indirect fetal electrocardiograms in order to achieve a signal-quality at least comparable to the direct ones. Method: Direct and indirect recordings, simultaneously acquired from 5 pregnant women during labor, were filtered with the Segmented-Beat Modulation Method and correlated in order to assess their morphological correspondence. Signal-to-noise ratio was used to quantify their quality. Results: Amplitude was higher in direct than indirect fetal electrocardiograms (median:104 µV vs. 22 µV; P=7.66·10-4), whereas noise was comparable (median:70 µV vs. 49 µV, P=0.45). Moreover, fetal electrocardiogram amplitude was significantly higher than affecting noise in direct recording (P=3.17·10-2) and significantly in indirect recording (P=1.90·10-3). Consequently, signal-to-noise ratio was initially higher for direct than indirect recordings (median:3.3 dB vs. -2.3 dB; P=3.90·10-3), but became lower after denoising of indirect ones (median:9.6 dB; P=9.84·10-4). Eventually, direct and indirect recordings were highly correlated (median: ρ=0.78; P<10-208), indicating that the two electrocardiograms were morphologically equivalent. Conclusion: Segmented-Beat Modulation Method is particularly useful for denoising of indirect fetal electrocardiogram and may contribute to the spread of this noninvasive technique in the clinical practice.

sEMG-Based Evaluation of Muscle Recruitment Variability During Walking in Terms of Activation Length and Occurrence Frequency

Surface electromyography (sEMG) is commonly used in gait analysis for detecting muscle activity in a non-invasive way, preserving the normal mobility of the subject. The purpose of the study was to assess the variability of sEMG signals acquired from lower-limb muscles during walking. To this aim, a statistical analysis of sEMG signals from a large number (hundreds) of strides per subject was performed in twenty-two healthy young caucasian volunteers. Tibialis Anterior, Gastrocnemius Lateralis, Rectus Femoris, Biceps Femoris and Vastus Lateralis were selected to represent both proximal and distal leg segments. Besides the muscular activation onset-offset instants, the study was aimed to analysed the occurrence frequency of muscle recruitment, a parameter seldom considered because of the low number of strides usually analysed in classic EMG studies. Findings illustrated that a single muscle showed a different number of activation intervals in different strides of the same walking. The number of times when muscle activates during a single gait cycle defined the modality of muscle recruitment, that in the present study was referred to as activation modality, i.e. n-activation modality consists of n-activation intervals for the considered muscle, during a single gait cycle. For each of the selected muscles, five activation modalities were detected. Each of these activation modalities is characterized by a different occurrence frequency and by different onset-offset activation instants. Concomitance of these results indicates a large variability in onset-offset muscular activation and occurrence frequency, which should be considered in discriminating pathological from physiological behaviour and for designing focused gait studies.

A stereophotogrammetric-based method to assess spatio-temporal gait parameters on healthy and Parkinsonian subjects.

Generally, the study of gait requires the detection of successive heel contacts and toe-off instants. Traditional gait analysis methods obtain these gait events using dynamometric platforms together with stereophotogrammetric data. Usually, are kept valid only those walking trials where the subjects step on each platform by only one foot. For subjects suffering from walking impairments it is very difficult or sometimes impossible to walk naturally and step properly on the dynamometric platforms. The aim of the present study is to propose a new method to identify, in an automatic manner, the initial contact (IC) and the toe-off (TO) time instants using only stereophotogrammetric data and a classic gait analysis protocol. The assessment of spatio-temporal gait variables during natural walking is also performed. The study consisted in analyzing healthy and Parkinsonian elderly subjects. The reliability of the proposed stereophotogrammetric-based method was tested by direct comparison with the IC and TO instants determined by the dynamometric platform data. The absence of any statistically significant differences between the values estimated by the two different modalities, highlights the reliability of the proposed method in the assessment of these two gait events. Results underline, as expected, the reduction of walking velocity in pathological patients during free ambulation. The present study proposes this method as a valid alternative to the traditional technique that use dynamometric platforms to identify main gait events, for subjects unable to walk naturally and to step properly on the platforms.

Association between Accelerations and Decelerations of Fetal Heart Rate

Cardiotocography (CTG) is the most popular test for establishing the fetal health status. Among its characterizing features there are the fetal heart rate (FHR) accelerations (ACC), usually considered a sign of fetal well-being; and decelerations (DEC), some of which may indicate the risk of fetal hypoxia. Thus, ACC and DEC are usually considered independent phenomena possibly providing opposite information on the fetus clinical status. CTG is typically analyzed by visual inspection; still a computerized analysis may provide a more objective CTG interpretation and precise ACC and DEC characterization. Aim of the present study is to propose an automatic procedure for ACC and DEC identification and characterization, and to investigate a potential relationship between their occurrence. The 552 tracings of the Physionet “CTU-CHB intrapartum CTG database” were analyzed according to a procedure that includes: FHR pre-processing; 20 min windowing; baseline estimation; and ACC and DEC identification and characterization. Specifically, ACC and DEC were defined as FHR deviations from baseline of at least 15 bpm for at least 15 s and then characterized in terms of length (s), amplitude (bpm) and area (length.amplitude; bpm.s). Only 383 (69.4%) CTG recordings showed sufficiently good FHR signal quality to be enrolled in the study. Number of DEC per window was significantly higher than ACC (4.0 vs 2.5; P<10-14). DEC were characterized by a comparable length but high-er amplitude and area than ACC (LNG: 56 s vs 61 s, P=0.2573; AMP: 12 bpm vs 10 bpm, P<10-11; AREA: 688 s·bpm vs 618 s·bpm, P=0.0032). DEC total area in a 20-min window was higher than that of ACC (3074 s·bpm vs 2007 s·bpm, P<10-9), but such areas were also strictly correlated (ρ=0.72; P<10-62). Thus, in a CTG recording, ACC and DEC are not independent phenomena but their occurrence is strictly associated.