Osteoporosis is a silent disease without any evidence of disease until a fracture occurs. Approximately 200 million people in the world are affected by osteoporosis and 8.9 million fractures occur each year worldwide. Fractures of the hip are a major public health burden, by means of both social cost and health condition of the elderly because these fractures are one of the main causes of morbidity, impairment, decreased quality of life and mortality in women and men. The aim of this review is to analyze the most important factors related to the enormous impact of osteoporotic fractures on population. Among the most common risk factors, low body mass index; history of fragility fracture, environmental risk, early menopause, smoking, lack of vitamin D, endocrine disorders (for example insulin-dependent diabetes mellitus), use of glucocorticoids, excessive alcohol intake, immobility and others represented the main clinical risk factors associated with augmented risk of fragility fracture. The increasing trend of osteoporosis is accompanied by an underutilization of the available preventive strategies and only a small number of patients at high fracture risk are recognized and successively referred for therapy. This report provides analytic evidences to assess the best practices in osteoporosis management and indications for the adoption of a correct healthcare strategy to significantly reduce the osteoporosis burden. Early diagnosis is the key to resize the impact of osteoporosis on healthcare system. In this context, attention must be focused on the identification of high fracture risk among osteoporotic patients. It is necessary to increase national awareness campaigns across countries in order to reduce the osteoporotic fractures incidence.

Major osteoporotic fragility fractures: Risk factor updates and societal impact

Bone biomarkers included formation, resorption and regulator are released during the bone remodeling processes. These bone biomarkers have attracted much attention in the clinical assessment of osteoporosis treatment in the past decade. Combination with the measurement of bone mineral density, the clinical applications of bone biomarkers have provided comprehensive information for diagnosis of osteoporosis. However, the analytical approaches of the bone biomarkers are still the challenge for further clinical trials. In this mini-review, we have introduced the functions of bone biomarkers and then recently developed techniques for bone biomarker measurements have been systematically integrated to discuss the possibility for osteoporosis assessment in the early stage.

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Bone biomarker for the clinical assessment of osteoporosis: recent developments and future perspectives

Objective. A signal-based metric for assessment of accuracy of motor unit (MU) identification from high-density surface electromyograms (EMG) is introduced. This metric, so-called pulse-to-noise-ratio (PNR), is computationally efficient, does not require any additional experimental costs and can be applied to every MU that is identified by the previously developed convolution kernel compensation technique. Approach. The analytical derivation of the newly introduced metric is provided, along with its extensive experimental validation on both synthetic and experimental surface EMG signals with signal-to-noise ratios ranging from 0 to 20 dB and muscle contraction forces from 5% to 70% of the maximum voluntary contraction. Main results. In all the experimental and simulated signals, the newly introduced metric correlated significantly with both sensitivity and false alarm rate in identification of MU discharges. Practically all the MUs with PNR > 30 dB exhibited sensitivity >90% and false alarm rates <2%. Therefore, a threshold of 30 dB in PNR can be used as a simple method for selecting only reliably decomposed units. Significance. The newly introduced metric is considered a robust and reliable indicator of accuracy of MU identification. The study also shows that high-density surface EMG can be reliably decomposed at contraction forces as high as 70% of the maximum.

http://iopscience.iop.org/article/10.1088/1741-2560/11/1/016008/pdf

Accurate identification of motor unit discharge patterns from high-density surface EMG and validation with a novel signal-based performance metric

https://research.aalto.fi/files/11701996/1_s2.0_S174680941500021X_main.pdf

Current state of digital signal processing in myoelectric interfaces and related applications

Hand prostheses controlled by surface electromyography are promising due to the non-invasive approach and the control capabilities offered by machine learning. Nevertheless, dexterous prostheses are still scarcely spread due to control difficulties, low robustness and often prohibitive costs. Several sEMG acquisition setups are now available, ranging in terms of costs between a few hundred and several thousand dollars. The objective of this paper is the relative comparison of six acquisition setups on an identical hand movement classification task, in order to help the researchers to choose the proper acquisition setup for their requirements. The acquisition setups are based on four different sEMG electrodes (including Otto Bock, Delsys Trigno, Cometa Wave + Dormo ECG and two Thalmic Myo armbands) and they were used to record more than 50 hand movements from intact subjects with a standardized acquisition protocol. The relative performance of the six sEMG acquisition setups is compared on 41 identical hand movements with a standardized feature extraction and data analysis pipeline aimed at performing hand movement classification. Comparable classification results are obtained with three acquisition setups including the Delsys Trigno, the Cometa Wave and the affordable setup composed of two Myo armbands. The results suggest that practical sEMG tests can be performed even when costs are relevant (e.g. in small laboratories, developing countries or use by children). All the presented datasets can be used for offline tests and their quality can easily be compared as the data sets are publicly available.

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Comparison of six electromyography acquisition setups on hand movement classification tasks.

This article is the first section of a review work structured in three parts and concerning a) advances in surface EMG detection and processing techniques, b) recent progress in surface EMG clinical research applications and, c) myoelectric control in neurorehabilitation. This article deals with the state of the art regarding a) the electrode-skin interface (equivalent circuits, skin treatment, conductive gels), b) signal detection modalities, spatial filters and front-end amplifiers, c) power line interference removal, separation of propagating and non-propagating potentials and removal of outliers from surface EMG signal maps, d) segmentation of surface EMG signal maps, e) decomposition of surface EMG into the constituent action potential trains, and f) relationship between surface EMG and force. The material is presented with an effort to fill gaps left by previous reviews and identify areas open for future research.

Advances in surface EMG: recent progress in detection and processing techniques.

We investigated the possible clinical feasibility and accuracy of an innovative ultrasound (US) method for diagnosis of osteoporosis of the spine. A total of 342 female patients (aged 51-60 y) underwent spinal dual X-ray absorptiometry and abdominal echographic scanning of the lumbar spine. Recruited patients were subdivided into a reference database used for US spectral model construction and a study population for repeatability and accuracy evaluation. US images and radiofrequency signals were analyzed via a new fully automatic algorithm that performed a series of spectral and statistical analyses, providing a novel diagnostic parameter called the osteoporosis score (O.S.). If dual X-ray absorptiometry is assumed to be the gold standard reference, the accuracy of O.S.-based diagnoses was 91.1%, with k = 0.859 (p < 0.0001). Significant correlations were also found between O.S.-estimated bone mineral densities and corresponding dual X-ray absorptiometry values, with r(2) values up to 0.73 and a root mean square error of 6.3%-9.3%. The results obtained suggest that the proposed method has the potential for future routine application in US-based diagnosis of osteoporosis.

A novel ultrasound methodology for estimating spine mineral density.

Aim of this study was to perform a detailed clinical validation of a new fully automatic algorithm for vertebral interface segmentation in echographic images. Abdominal echographic scans of lumbar vertebrae L1–L4 were carried out on 150 female subjects with variable age and body mass index (BMI). Acquired datasets were automatically processed by the algorithm and the accuracy of the obtained segmentations was then evaluated by three independent experienced operators. Obtained results showed a very good specificity in vertebra detection (93.3%), coupled with a reasonable sensitivity (68.1%), representing a suitable compromise between the detection of a sufficient number of vertebrae for reliable diagnoses and the limitation of the corresponding computation time. Importantly, there was only a minimum presence of ‘false vertebrae’ detected (2.8%), resulting in a very low influence on subsequent diagnostic analyses. Furthermore, the algorithm was specifically tuned to provide an improved sensitivity (up to 73.1%) with increasing patient BMI, to keep a suitable number of correctly detected vertebrae even when the acquisition was intrinsically more difficult because of the augmented thickness of abdominal soft tissues. The proposed algorithm will represent an essential added value for developing echographic methods for the diagnosis of osteoporosis on lumbar vertebrae.

Validation of an automatic segmentation method to detect vertebral interfaces in ultrasound images

Early diagnosis and continuous monitoring of respiratory failure (RF) in the course of the most prevalent chronic cardio-vascular (CVD) and respiratory diseases (CRD) are a clinical, unresolved problem because wearable, non-invasive, and user-friendly medical devices, which could grant reliable measures of the oxygen saturation (SpO2) and heart rate (HR) in real-life during daily activities are still lacking. In this study, we investigated the agreement between a new medical wrist-worn device (BrOxy M) and a reference, medical pulseoximeter (Nellcor PM 1000N). Twelve healthy volunteers (aged 20–51 years, 84% males, 33% with black skin, obtaining, during the controlled hypoxia test, the simultaneous registration of 219 data pairs, homogeneously deployed in the levels of Sat.O2 97%, 92%, 87%, 82% [ISO 80601-2-61:2017 standard (paragraph EE.3)]) were included. The paired T test 0 and the Bland-Altman plot were performed to assess bias and accuracy. SpO2 and HR readings by the two devices resulted significantly correlated (r = 0.91 and 0.96, p < 0.001, respectively). Analyses excluded the presence of proportional bias. For SpO2, the mean bias was −0.18% and the accuracy (ARMS) was 2.7%. For HR the mean bias was 0.25 bpm and the ARMS3.7 bpm. The sensitivity to detect SpO2 ≤ 94% was 94.4%. The agreement between BrOxy M and the reference pulse oximeter was “substantial” (for SpO2 cut-off 94% and 90%, k = 0.79 and k = 0.80, respectively). We conclude that BrOxy M demonstrated accuracy, reliability and consistency in measuring SpO2 and HR, being fully comparable with a reference medical pulseoxymeter, with no adverse effects. As a wearable device, Broxy M can measure continually SpO2 and HR in everyday life, helping in detecting and following up CVD and CRD subjects.

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Matteo Aventaggiato

Papers

Advances in surface EMG: recent progress in detection and processing techniques.

A novel ultrasound methodology for estimating spine mineral density.

Validation of an automatic segmentation method to detect vertebral interfaces in ultrasound images

Accuracy of a New Pulse Oximetry in Detection of Arterial Oxygen Saturation and Heart Rate Measurements: The SOMBRERO Study