To study in-depth characteristics of single bicycle crashes and type of injuries considering gender and age differences.
Hospital reported bicycle crashes identified in the Swedish national database ...STRADA were combined with self-reported detailed information regarding crash circumstances and injury outcomes. Gender and age-group differences were investigated using univariate statistics and Pearson Chi- Square test.
A total of 616 cyclists injured in single bicycle crashes between 2013 and 2017 were included. Participants (49% women) had a mean age of 58 years (ranged 15–89 years), most rode a comfort bike (54%) and cycled several times a week (81%). The most common crash type was skidding on ice or snow (26%). This crash type was significantly more common among women than men (30% versus 21%). Women more than twice as often lost balance at low or no speed (13% versus 5%). While men's injuries were located more than twice as often at shoulder and upper arm (28% versus 11%), women injured more than four times as often the lower leg and ankle (30% versus 7%). Differences regarding age-groups could be observed as an exponential increase of hip and upper leg injuries with increased age (9, 19 and 38%). Older cyclists were more often injured while losing balance at no or low speed and while getting on or off the bicycle.
Concrete countermeasures to prevent injuries in single bicycle crashes can be suggested and directed to different target groups, i.e. women or men or younger or elderly.
•Elderly and female cyclists were more often involved in crashes with no or low speed.•Shoulder and upper arm injuries were more common among men.•Women injured more often lower leg and ankle and elderly mainly hip and upper leg.•To prevent traumatic brain injuries, stationary objects as well as slippery surfaces should be avoided.•Preventing shoulder and upper arm injuries needs additionally focus on curbstone design.
Innovative technologies in dermatology allow for the early screening of skin cancer, which results in a reduction in the mortality rate and surgical treatments. The diagnosis of melanoma is complex ...not only because of the number of different lesions but because of the high similarity amongst skin lesions of different nature; hence, human vision and physician experience still play a major role. The adoption of automatic systems would aid clinical assessment and make the diagnosis reproducible by eliminating inter- and intra-observer variabilities. In our paper, we describe a computer-aided system for the early diagnosis of melanoma in dermoscopic images. A soft pre-processing phase is performed so as to avoid the loss of details both in texture, colors, and contours, and color-based image segmentation is later carried out using k-means. Features linked to both geometric properties and color characteristics are used to analyze skin lesions through a support vector machine classifier. The PH2 public database is used for the assessment of the procedure’s sensitivity, specificity, and accuracy. A statistical approach is carried out to establish the impact of image quality on performance. The obtained results show remarkable achievements, so our computer-aided approach should be suitable as a Decision Support System for melanoma detection.
The establishment of automatic diagnostic systems able to detect and classify skin lesions at the initial stage are getting really relevant and effective in providing support for medical personnel ...during clinical assessment. Image segmentation has a determinant part in computer-aided skin lesion diagnosis pipeline because it makes possible to extract and highlight information on lesion contour texture as, for example, skewness and area unevenness. However, artifacts, low contrast, indistinct boundaries, and different shapes and areas contribute to make skin lesion segmentation a challenging task. In this paper, a fully automatic computer-aided system for skin lesion segmentation in dermoscopic images is indicated. Adopting this method, noise and artifacts are initially reduced by the singular value decomposition; afterward lesion decomposition into a frame of bit-plane layers is performed. A specific procedure is implemented for redundant data reduction using simple Boolean operators. Since lesion and background are rarely homogeneous regions, the obtained segmentation region could contain some disjointed areas classified as lesion. To obtain a single zone classified as lesion avoiding spurious pixels or holes inside the image under test, mathematical morphological techniques are implemented. The performance obtained highlights the method validity.
Cardiac signal processing is usually a computationally demanding task as signals are heavily contaminated by noise and other artifacts. In this paper, an effective approach for peak point detection ...and localization in noisy electrocardiogram (ECG) signals is presented. Six stages characterize the implemented method, which adopts the Hilbert transform and a thresholding technique for the detection of zones inside the ECG signal which could contain a peak. Subsequently, the identified zones are analyzed using the wavelet transform for R point detection and localization. The conceived signal processing technique has been evaluated, adopting ECG signals belonging to MIT-BIH Noise Stress Test Database, which includes specially selected Holter recordings characterized by baseline wander, muscle artifacts and electrode motion artifacts as noise sources. The experimental results show that the proposed method reaches most satisfactory performance, even when challenging ECG signals are adopted. The results obtained are presented, discussed and compared with some other R wave detection algorithms indicated in literature, which adopt the same database as a test bench. In particular, for a signal to noise ratio (SNR) equal to 6 dB, results with minimal interference from noise and artifacts have been obtained, since Se e +P achieve values of 98.13% and 96.91, respectively.
Structures for the evaluation of fast Fourier transforms are important components in several signal-processing applications and communication systems. Their capabilities play a key role in the ...performance enhancement of the whole system in which they are embedded. In this paper, a novel implementation of the discrete Fourier transform is proposed, based on a bit-slice approach and on the exploitation of the input sequence finite word length. Input samples of the sequence to be transformed are split into binary sequences and each one is Fourier transformed using only complex sums. An FPGA-based solution characterized by low latency and low power consumption is designed. Simulations have been carried out, first in the Matlab environment, then emulated in Quartus IDE with Intel. The hardware implementation of the conceived system and the test for the functional accuracy verification have been performed, adopting the DE2-115 development board from Terasic, which is equipped with the Cyclone IV EP4CE115F29C7 FPGA by Intel.
FPGA-Based Decision Support System for ECG Analysis Giorgio, Agostino; Guaragnella, Cataldo; Rizzi, Maria
Journal of low power electronics and applications,
01/2023, Letnik:
13, Številka:
1
Journal Article
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The high mortality rate associated with cardiac abnormalities highlights the need of accurately detecting heart disorders in the early stage so to avoid severe health consequence for patients. Health ...trackers have become popular in the form of wearable devices. They are aimed to perform cardiac monitoring outside of medical clinics during peoples’ daily lives. Our paper proposes a new diagnostic algorithm and its implementation adopting a FPGA-based design. The conceived system automatically detects the most common arrhythmias and is also able to evaluate QT-segment lengthening and pulmonary embolism risk often caused by myocarditis. Debug and simulations have been carried out firstly in Matlab environment and then in Quartus IDE by Intel. The hardware implementation of the embedded system and the test for the functional accuracy verification have been performed adopting the DE1_SoC development board by Terasic, which is equipped with the Cyclone V 5CSEMA5F31C6 FPGA by Intel. Properly modified real ECG signals corrupted by a mixture of muscle noise, electrode movement artifacts, and baseline wander are used as a test bench. A value of 99.20% accuracy is achieved by taking into account 0.02 mV for the root mean square value of noise voltage. The implemented low-power circuit is suitable as a wearable decision support device.
The interest of the scientific community for computer aided skin lesion analysis and characterization has been increased during the last years for the growing incidence of melanoma among cancerous ...pathologies. The detection of melanoma in its early stage is essential for prognosis improvement and for guaranteeing a high five-year relative survival rate of patients. The clinical diagnosis of skin lesions is challenging and not trivial since it depends on human vision and physician experience and expertise. Therefore, a computer method that makes an accurate extraction of important details of skin lesion image can assist dermatologists in cancer detection. In particular, the border detection is a critical computer vision issue owing to the wide range of lesion shapes, sizes, colours and skin texture types. In this paper, an automatic and effective pigmented skin lesion segmentation method in dermoscopic image is presented. The proposed procedure is adopted to extract a mask of the lesion region without the adoption of other signal processing procedures for image improvement. A quantitative experimental evaluation has been performed on a publicly available database. The achieved results show the method validity and its high robustness towards irregular boundaries, smooth transition between lesion and skin, noise and artifact presence.
Objective: As bicyclists account for the largest share of serious injuries in Sweden, focus to improve safety for bicyclists is needed. While knowledge about fatal bicycle crashes is rather ...extensive, the number of studies that have investigated non-fatal injuries is still rather limited. The aim of this study was to estimate the potential of different countermeasures to reduce crashes resulting in injuries with high risk of health-loss among cyclists in Sweden. A further aim was to describe the residual-that is, crashes that were not considered to be addressed by the analyzed countermeasures.
Methods: A sample of individuals with specific injury diagnoses was drawn from the Swedish national crash database Strada. A survey form was used to collect additional information about the crash and the health-related outcomes. The potential of countermeasures currently included in the Swedish Safety Performance Indicators, as well as of countermeasures that could be described as "existing but not fully implemented" was assessed. The overall potential of all countermeasures assessed was calculated, giving a grand total without double counting. Cases that were considered not to be addressed by any of the countermeasures included (i.e., the residual crashes) were described in more detail.
Results: The current Swedish Safety Performance Indicators that relate to safe cycling addressed 22% of crashes. Improved maintenance by deicing and removal of snow from bicycle infrastructure was found to have the highest potential (8%), followed by improved crashworthiness of passenger cars (5%) and safer bicycle crossings (4%). The potential for existing but not fully implemented safety improvements was 56%. The greatest potential was found for Autonomous Emergency Braking with cyclist detection for passenger cars (12%), followed by studded winter tyres for bicycles (12%), and improved maintenance on non-bicycle infrastructure (11%). In total, taking double counting into consideration, all safety improvements could address 64% of all crashes. Among the residual crashes, the majority (69%) were single bicycle crashes of which most were related to wheel locking during braking and losing balance at low speed or stationary.
Conclusions: Compared with fatal crashes that involve a majority of bicycle-car crashes, the crashes leading to health-loss are mostly single bicycle crashes. Therefore, innovation and development of additional countermeasures to improve safety for bicyclists should focus on single bicycle crashes.
The analysis of cardiac signals is still regarded as attractive by both the academic community and industry because it helps physicians in detecting abnormalities and improving the diagnosis and ...therapy of diseases. Electrocardiographic signal processing for detecting irregularities related to the occurrence of low-amplitude waveforms inside the cardiac signal has a considerable workload as cardiac signals are heavily contaminated by noise and other artifacts. This paper presents an effective approach for the detection of ventricular late potential occurrences which are considered as markers of sudden cardiac death risk. Three stages characterize the implemented method which performs a beat-to-beat processing of high-resolution electrocardiograms (HR-ECG). Fifteen lead HR-ECG signals are filtered and denoised for the improvement of signal-to-noise ratio. Five features were then extracted and used as inputs of a classifier based on a machine learning approach. For the performance evaluation of the proposed method, a HR-ECG database consisting of real ventricular late potential (VLP)-negative and semi-simulated VLP-positive patterns was used. Experimental results show that the implemented system reaches satisfactory performance in terms of sensitivity, specificity accuracy, and positive predictivity; in fact, the respective values equal to 98.33%, 98.36%, 98.35%, and 98.52% were achieved.
This study has analyzed sex-specific differences in pedestrian and cyclist accidents involving passenger cars. The most frequently injured body regions, types of injuries, which show sex-specific ...differences and the general accident parameters of females and males were compared. Accident data from three different European countries (Austria, Netherlands, Sweden) were analyzed. The current analysis shows that for both, females and males, pedestrian and cyclist injuries are sustained mainly to the body regions head, thorax, upper extremities and lower extremities. The results show that the odds for sustaining skeletal injuries to the lower extremities (incl. pelvis) in females are significantly higher. It was observed in all datasets, that the odds of females being involved in a rural accident or an accident at night are lower than for males. Elderly pedestrian and cyclist (≥60YO) tend to sustain more severe injuries (AIS2+ and AIS3+) than younger pedestrian and cyclists (<60YO) in some of the datasets. The findings of this study highlight the differences in males and females in both, accident scenarios and sustained injuries. Further investigations are needed to distinguish between gender- and sex-specific differences causing the different injury patterns.
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