Evaluation of classification performance in human lower limb jump phases of signal correlation information and LSTM models

2021 ◽  
Vol 64 ◽  
pp. 102279 ◽  
Author(s):  
Yanzheng Lu ◽  
Hong Wang ◽  
Yangyang Qi ◽  
Hailong Xi
Keyword(s):  
Lower Limb ◽  
Classification Performance ◽  
Correlation Information ◽  
Signal Correlation

Variability in Muscle Recruitment Strategy Between Operators During Assisted Assembly Tasks

2018 ◽  
Author(s):  
Yingxin Qiu ◽  
Keerthana Murali ◽  
Jun Ueda ◽  
Atsushi Okabe ◽  
Dalong Gao
Keyword(s):  
Upper Limb ◽  
Lower Limb ◽  
Wrist Joint ◽  
Principal Component ◽  
Classification Performance ◽  
Body Motion ◽  
Recruitment Strategy ◽  
Support Vector ◽  
Recruitment Strategies ◽  
Muscle Recruitment

This paper reports the variability in muscle recruitment strategies among individuals who operate a non-powered lifting device for general assembly (GA) tasks. Support vector machine (SVM) was applied to the classification of motion states of operators using electromyography (EMG) signals collected from a total of 15 upper limb, lower limb, shoulder, and torso muscles. By comparing the classification performance and muscle activity features, variability in muscle recruitment strategy was observed from lower limb and torso muscles, while the recruitment strategies of upper limb and shoulder muscles were relatively consistent across subjects. Principal component analysis (PCA) was applied to identify key muscles that are highly correlated with body movements. Selected muscles at the wrist joint, ankle joint and scapula are considered to have greater significance in characterizing the muscle recruitment strategies than other investigated muscles. PCA loading factors also indicate the existence of body motion redundancy during typical pick-and-place tasks.

Enhanced deep residual network with multilevel correlation information for fault diagnosis of rotating machinery

2020 ◽  
pp. 107754632094971 ◽  
Author(s):  
Shoucong Xiong ◽  
Shuai He ◽  
Jianping Xuan ◽  
Qi Xia ◽  
Tielin Shi
Keyword(s):  
Deep Learning ◽  
Fault Diagnosis ◽  
Wavelet Packet ◽  
Learning Algorithms ◽  
Vibration Signal ◽  
Rolling Bearing ◽  
Classification Performance ◽  
Residual Network ◽  
Time Frequency ◽  
Correlation Information

Modern machinery becomes more precious with the advance of science, and fault diagnosis is vital for avoiding economical losses or casualties. Among massive diagnosis methods, deep learning algorithms stand out to open an era of intelligent fault diagnosis. Deep residual networks are the state-of-the-art deep learning models which can continuously improve performance by deepening the network structures. However, in vibration-based fault diagnosis, the transient property instability of vibration signal usually calls for time–frequency analysis methods, and the characters of time–frequency matrices are distinct from standard images, which brings some natural limitations for the diagnosis performance of deep learning algorithms. To handle this issue, an enhanced deep residual network named the multilevel correlation stack-deep residual network is proposed in this article. Wavelet packet transform is used to preprocess the sensor signal, and then the proposed multilevel correlation stack-deep residual network uses kernels with different shapes to fully dig various kinds of useful information from any local regions of the processed input. Experiments on two rolling bearing datasets are carried out. Test results show that the multilevel correlation stack-deep residual network exhibits a more satisfactory classification performance than original deep residual networks and other similar methods, revealing significant potentials for realistic fault diagnosis applications.

scholarly journals Hyperspectral Image Classification via Multi-Feature-Based Correlation Adaptive Representation

2021 ◽  
Vol 13 (7) ◽  
pp. 1253
Author(s):  
Guichi Liu ◽  
Lei Gao ◽  
Lin Qi
Keyword(s):  
Tikhonov Regularization ◽  
Hyperspectral Image ◽  
Training Sample ◽  
Classification Performance ◽  
Collaborative Representation ◽  
Data Correlation ◽  
Adaptive Representation ◽  
Training Samples ◽  
Distance Weighted ◽  
Correlation Information

In recent years, representation-based methods have attracted more attention in the hyperspectral image (HSI) classification. Among them, sparse representation-based classifier (SRC) and collaborative representation-based classifier (CRC) are the two representative methods. However, SRC only focuses on sparsity but ignores the data correlation information. While CRC encourages grouping correlated variables together but lacks the ability of variable selection. As a result, SRC and CRC are incapable of producing satisfied performance. To address these issues, in this work, a correlation adaptive representation (CAR) is proposed, enabling a CAR-based classifier (CARC). Specifically, the proposed CARC is able to explore sparsity and data correlation information jointly, generating a novel representation model that is adaptive to the structure of the dictionary. To further exploit the correlation between the test samples and the training samples effectively, a distance-weighted Tikhonov regularization is integrated into the proposed CARC. Furthermore, to handle the small training sample problem in the HSI classification, a multi-feature correlation adaptive representation-based classifier (MFCARC) and MFCARC with Tikhonov regularization (MFCART) are presented to improve the classification performance by exploring the complementary information across multiple features. The experimental results show the superiority of the proposed methods over state-of-the-art algorithms.

The chronically ischemic lower limb

JAMA ◽  
1966 ◽  
Vol 197 (11) ◽  
pp. 915-916
Author(s):  
I. J. Schatz
Keyword(s):  
Lower Limb

Cardiac troponin I in patients with acute upper and lower limb ischemia

VASA ◽  
2008 ◽  
Vol 37 (4) ◽  
pp. 327-332 ◽  
Author(s):  
Koutouzis ◽  
Sfyroeras ◽  
Moulakakis ◽  
Kontaras ◽  
Nikolaou ◽  
...  
Keyword(s):  
Upper Limb ◽  
Lower Limb ◽  
Cardiac Troponin ◽  
Cardiac Involvement ◽  
Troponin I ◽  
Limb Ischemia ◽  
Elevated Troponin ◽  
Troponin Elevation ◽  
Lower Limb Ischemia ◽  
Ischemia Group

Background: The aim of this study was to investigate the presence, etiology and clinical significance of elevated troponin I in patients with acute upper or lower limb ischemia. The high sensitivity and specificity of cardiac troponin for the diagnosis of myocardial cell damage suggested a significant role for troponin in the patients investigated for this condition. The initial enthusiasm for the diagnostic potential of troponin was limited by the discovery that elevated cardiac troponin levels are also observed in conditions other than acute myocardial infarction, even conditions without obvious cardiac involvement. Patients and Methods: 71 consecutive patients participated in this study. 31 (44%) of them were men and mean age was 75.4 ± 10.3 years (range 44–92 years). 60 (85%) patients had acute lower limb ischemia and the remaining (11; 15%) had acute upper limb ischemia. Serial creatine kinase (CK), isoenzyme MB (CK-MB) and troponin I measurements were performed in all patients. Results: 33 (46%) patients had elevated peak troponin I (> 0.2 ng/ml) levels, all from the lower limb ischemia group (33/60 vs. 0/11 from the acute upper limb ischemia group; p = 0.04). Patients with lower limb ischemia had higher peak troponin I values than patients with upper limb ischemia (0.97 ± 2.3 [range 0.01–12.1] ng/ml vs. 0.04 ± 0.04 [0.01–0.14] ng/ml respectively; p = 0.003), higher peak CK values (2504 ± 7409 [range 42–45 940] U/ml vs. 340 ± 775 [range 34–2403] U/ml, p = 0.002, respectively, in the two groups) and peak CK-MB values (59.4 ± 84.5 [range 12–480] U/ml vs. 21.2 ± 9.1 [range 12–39] U/ml, respectively, in the two groups; p = 0.04). Peak cardiac troponin I levels were correlated with peak CK and CK-MB values. Conclusions: Patients with lower limb ischemia often have elevated troponin I without a primary cardiac source; this was not observed in patients presenting with acute upper limb ischemia. It is very important for these critically ill patients to focus on the main problem of acute limb ischemia and to attempt to treat the patient rather than the troponin elevation per se. Cardiac troponin elevation should not prevent physicians from providing immediate treatment for limb ischaemia to these patients, espescially when signs, symptoms and electrocardiographic findings preclude acute cardiac involvement.

Acute limb ischemia in a patient with pre-fibrotic myelofibrosis complicated by heparin-induced thrombocytopenia and thrombosis – case report and systematic review of dabigatran use

VASA ◽  
2020 ◽  
pp. 1-6 ◽  
Author(s):  
Marina Di Pilla ◽  
Stefano Barco ◽  
Clara Sacco ◽  
Giovanni Barosi ◽  
Corrado Lodigiani
Keyword(s):  
Systematic Review ◽  
Case Report ◽  
Lower Limb ◽  
Limb Ischemia ◽  
Acute Limb Ischemia ◽  
Review Of The Literature ◽  
Heparin Induced Thrombocytopenia ◽  
Lower Limb Ischemia ◽  
Vein Thrombosis ◽  
Left Lower Limb

Summary: A 49-year-old man was diagnosed with pre-fibrotic myelofibrosis after acute left lower-limb ischemia requiring amputation and portal vein thrombosis. After surgery he developed heparin-induced thrombocytopenia (HIT) with venous thromboembolism, successfully treated with argatroban followed by dabigatran. Our systematic review of the literature supports the use of dabigatran for suspected HIT.

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