1,721,033 research outputs found
Dimensionality reduction for the quantitative evaluation of a smartphone-based Timed Up and Go test
No full textThe Timed Up and Go is a clinical test to assess mobility in the elderly and in Parkinson's disease. Lately instrumented versions of the test are being considered, where inertial sensors assess motion. To improve the pervasiveness, ease of use, and cost, we consider a smartphone's accelerometer as the measurement system. Several parameters (usually highly correlated) can be computed from the signals recorded during the test. To avoid redundancy and obtain the features that are most sensitive to the locomotor performance, a dimensionality reduction was performed through principal component analysis (PCA). Forty-nine healthy subjects of different ages were tested. PCA was performed to extract new features (principal components) which are not redundant combinations of the original parameters and account for most of the data variability. They can be useful for exploratory analysis and outlier detection. Then, a reduced set of the original parameters was selected through correlation analysis with the principal components. This set could be recommended for studies based on healthy adults. The proposed procedure could be used as a first-level feature selection in classification studies (i.e. healthy-Parkinson's disease, fallers-non fallers) and could allow, in the future, a complete system for movement analysis to be incorporated in a smartphone
Quality Assessment and Morphological Analysis of Photoplethysmography in Daily Life
Full text linkThe photoplethysmographic (PPG) signal has been applied in various research fields, with promising results for its future clinical application. However, there are several sources of variability that, if not adequately controlled, can hamper its application in pervasive monitoring contexts. This study assessed and characterized the impact of several sources of variability, such as physical activity, age, sex, and health state on PPG signal quality and PPG waveform parameters (Rise Time, Pulse Amplitude, Pulse Time, Reflection Index, Delta T, and DiastolicAmplitude). We analyzed 31 24 h recordings by as many participants (19 healthy subjects and 12 oncological patients) with a wristband wearable device, selecting a set of PPG pulses labeled with three different quality levels. We implemented a Multinomial Logistic Regression (MLR) model to evaluate the impact of the aforementioned factors on PPG signal quality. We then extracted six parameters only on higher-quality PPG pulses and evaluated the influence of physical activity, age, sex, and health state on these parameters with Generalized Linear Mixed Effects Models (GLMM). We found that physical activity has a detrimental effect on PPG signal quality quality (94% of pulses with good quality when the subject is at rest vs. 9% during intense activity), and that health state affects the percentage of available PPG pulses of the best quality (at rest, 44% for healthy subjects vs. 13% for oncological patients). Most of the extracted parameters are influenced by physical activity and health state, while age significantly impacts two parameters related to arterial stiffness. These results can help expand the awareness that accurate, reliable information extracted from PPG signals can be reached by tackling and modeling different sources of inaccuracy
Physical activity classification using body-worn inertial sensors in a multi-sensor setup
No full textPhysical inactivity significantly impacts personal health, reduces quality of life, and often leads to mobility disorders, diabetes, and cardiovascular disease. Monitoring daily life activities by means of wearable inertial sensors can provide valuable feedback necessary to improve the quality of daily life and prevent the development of mobility disorders caused by physical inactivity. In this study, a physical activity classification (PAC) algorithm was developed and tested using an inertial sensor-based dataset. The dataset was acquired from multiple inertial sensors, each mounted at a different body location, and consists of various Activities of Daily Living (ADL). Data from nineteen healthy young subjects were analyzed. Time- and frequency-domain features from raw 3D accelerometer and 3D gyroscope signals were computed by performing windowing of the time series data. The K-nearest neighbors (KNN) pattern recognition algorithm was used to classify thirteen different ADLs and was evaluated by a 10-fold cross-validation. The proposed PAC algorithm outperformed the existing algorithm validated using the same dataset, with an overall mean classification rate (sensitivity) of 97.38%. This paper discusses the limitations of this study and proposes ways to overcome said limitations in order to make the PAC algorithm more effective in real-life conditions
Assessing Gait in Parkinson’s Disease Using Wearable Motion Sensors: A Systematic Review
Full text linkAbstract: Parkinson’s disease (PD) is a progressive neurodegenerative disorder. Gait impairments are common among people with PD. Wearable sensor systems can be used for gait analysis by providing spatio-temporal parameters useful to investigate the progression of gait problems in Parkinson disease. However, various methods and tools with very high variability have been developed. The aim of this study is to review published articles of the last 10 years (from 2008 to 2018) concerning the application of wearable sensors to assess spatio-temporal parameters of gait in patients with PD. We focus on inertial sensors used for gait analysis in the clinical environment (i.e., we do not cover the use of inertial sensors to monitor walking or general activities at home, in unsupervised environments). Materials and Methods: Relevant articles were searched in the Medline database using Pubmed. Results and Discussion: Two hundred ninety-four articles were initially identified while searching the scientific literature regarding this topic. Thirty-six articles were selected and included in this review. Conclusion: Wearable motion sensors are useful, non-invasive, low-cost, and objective tools that are being extensively used to perform gait analysis on PD patients. Being able to diagnose and monitor the progression of PD patients makes wearable sensors very useful to evaluate clinical efficacy before and after therapeutic interventions. However, there is no uniformity in the use of wearable sensors in terms of: number of sensors, positioning, chosen parameters, and other characteristics. Future research should focus on standardizing the measurement setup and selecting which spatio-temporal parameters are the most informative to analyze gait in PD. These parameters should be provided as standard assessments in all studies to increase replicability and comparability of results
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
sj-pdf-1-tmj-10.1177_03008916211053048 – Supplemental material for Lung metastasectomy for osteosarcoma in children, adolescents, and young adults: proof of permanent cure
No full textSupplemental material, sj-pdf-1-tmj-10.1177_03008916211053048 for Lung metastasectomy for osteosarcoma in children, adolescents, and young adults: proof of permanent cure by Ugo Pastorino, Emanuela Palmerini, Luca Porcu, Roberto Luksch, Paolo Scanagatta, Cristina Meazza, Giovanni Leuzzi, Maura Massimino and Piero Picci in Tumori Journal</p
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Design of a High Bandwidth Actuation for Seamless Assistance in Walking and Running
No full textTo date, the majority of robotic assistive devices designed for lower limb support are tailored for either walking or running, with minimal exploration into devices capable of accommodating both activities. This discrepancy stems from the inherent differences in movement frequencies between walking and running, necessitating actuation systems with sufficient bandwidth to handle both tasks effectively. The challenge lies in addressing the faster reversal of electromechanical actuators' direction that accompanies increased frequencies. To tackle this challenge, our work introduces a novel underactuated actuation mechanism based on the Tusi Couple, specifically designed to support both walking and running in robotic assistive devices. This mechanism is designed to produce alternating motor motion at lower step frequencies associated with walking, and continuous motion at higher step frequencies associated with running, thereby minimizing delays related to motion alternation. In both cases, the mechanism converts the mentioned rotary movements of the motor into alternating linear movement of a slider as output. By aligning the mechanism's motion with the cyclic nature of human locomotion, our results suggest potential for providing timely assistance to human lower limbs. Upon integration into an embedded robotic wearable device, this actuation mechanism holds promise as a unified solution for assisting all human locomotion modes
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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