Artif Intell Med - A computer vision framework for finger-tapping evaluation in Parkinson's disease.

Tópicos

{ signal(2180) analysi(812) frequenc(800) }
{ featur(3375) classif(2383) classifi(1994) }
{ motion(1329) object(1292) video(1091) }
{ case(1353) use(1143) diagnosi(1136) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ high(1669) rate(1365) level(1280) }
{ decis(3086) make(1611) patient(1517) }
{ take(945) account(800) differ(722) }
{ care(1570) inform(1187) nurs(1089) }
{ system(1050) medic(1026) inform(1018) }
{ monitor(1329) mobil(1314) devic(1160) }
{ sampl(1606) size(1419) use(1276) }
{ spatial(1525) area(1432) region(1030) }
{ first(2504) two(1366) second(1323) }
{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ control(1307) perform(991) simul(935) }
{ compound(1573) activ(1297) structur(1058) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ result(1111) use(1088) new(759) }
{ system(1976) rule(880) can(841) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ learn(2355) train(1041) set(1003) }
{ concept(1167) ontolog(924) domain(897) }
{ method(1557) propos(1049) approach(1037) }
{ general(901) number(790) one(736) }
{ perform(999) metric(946) measur(919) }
{ studi(1119) effect(1106) posit(819) }
{ record(1888) medic(1808) patient(1693) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ model(2656) set(1616) predict(1553) }
{ age(1611) year(1155) adult(843) }
{ group(2977) signific(1463) compar(1072) }
{ data(3008) multipl(1320) sourc(1022) }
{ activ(1138) subject(705) human(624) }
{ can(981) present(881) function(850) }
{ structur(1116) can(940) graph(676) }
{ method(1969) cluster(1462) data(1082) }
{ detect(2391) sensit(1101) algorithm(908) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ bind(1733) structur(1185) ligand(1036) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ studi(2440) review(1878) systemat(933) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ extract(1171) text(1153) clinic(932) }
{ data(1714) softwar(1251) tool(1186) }
{ design(1359) user(1324) use(1319) }
{ model(2220) cell(1177) simul(1124) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ research(1085) discuss(1038) issu(1018) }
{ import(1318) role(1303) understand(862) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ perform(1367) use(1326) method(1137) }
{ blood(1257) pressur(1144) flow(957) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ ehr(2073) health(1662) electron(1139) }
{ patient(2837) hospit(1953) medic(668) }
{ data(2317) use(1299) case(1017) }
{ medic(1828) order(1363) alert(1069) }
{ cost(1906) reduc(1198) effect(832) }
{ gene(2352) biolog(1181) express(1162) }
{ intervent(3218) particip(2042) group(1664) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ cancer(2502) breast(956) screen(824) }
{ drug(1928) target(777) effect(648) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(2212) result(1239) propos(1039) }

Resumo

JECTIVES: The rapid finger-tapping test (RFT) is an important method for clinical evaluation of movement disorders, including Parkinson's disease (PD). In clinical practice, the naked-eye evaluation of RFT results in a coarse judgment of symptom scores. We introduce a novel computer-vision (CV) method for quantification of tapping symptoms through motion analysis of index-fingers. The method is unique as it utilizes facial features to calibrate tapping amplitude for normalization of distance variation between the camera and subject.METHODS: The study involved 387 video footages of RFT recorded from 13 patients diagnosed with advanced PD. Tapping performance in these videos was rated by two clinicians between the symptom severity levels ('0: normal' to '3: severe') using the unified Parkinson's disease rating scale motor examination of finger-tapping (UPDRS-FT). Another set of recordings in this study consisted of 84 videos of RFT recorded from 6 healthy controls. These videos were processed by a CV algorithm that tracks the index-finger motion between the video-frames to produce a tapping time-series. Different features were computed from this time series to estimate speed, amplitude, rhythm and fatigue in tapping. The features were trained in a support vector machine (1) to categorize the patient group between UPDRS-FT symptom severity levels, and (2) to discriminate between PD patients and healthy controls.RESULTS: A new representative feature of tapping rhythm, 'cross-correlation between the normalized peaks' showed strong Guttman correlation (?2=-0.80) with the clinical ratings. The classification of tapping features using the support vector machine classifier and 10-fold cross validation categorized the patient samples between UPDRS-FT levels with an accuracy of 88%. The same classification scheme discriminated between RFT samples of healthy controls and PD patients with an accuracy of 95%.CONCLUSION: The work supports the feasibility of the approach, which is presumed suitable for PD monitoring in the home environment. The system offers advantages over other technologies (e.g. magnetic sensors, accelerometers, etc.) previously developed for objective assessment of tapping symptoms.

Resumo Limpo

jectiv rapid fingertap test rft import method clinic evalu movement disord includ parkinson diseas pd clinic practic nakedey evalu rft result coars judgment symptom score introduc novel computervis cv method quantif tap symptom motion analysi indexfing method uniqu util facial featur calibr tap amplitud normal distanc variat camera subjectmethod studi involv video footag rft record patient diagnos advanc pd tap perform video rate two clinician symptom sever level normal sever use unifi parkinson diseas rate scale motor examin fingertap updrsft anoth set record studi consist video rft record healthi control video process cv algorithm track indexfing motion videofram produc tap timeseri differ featur comput time seri estim speed amplitud rhythm fatigu tap featur train support vector machin categor patient group updrsft symptom sever level discrimin pd patient healthi controlsresult new repres featur tap rhythm crosscorrel normal peak show strong guttman correl clinic rate classif tap featur use support vector machin classifi fold cross valid categor patient sampl updrsft level accuraci classif scheme discrimin rft sampl healthi control pd patient accuraci conclus work support feasibl approach presum suitabl pd monitor home environ system offer advantag technolog eg magnet sensor acceleromet etc previous develop object assess tap symptom

Resumos Similares

Med Biol Eng Comput - Pathological speech signal analysis and classification using empirical mode decomposition. ( 0,736572562177181 )
Comput Methods Programs Biomed - Neural network and wavelet average framing percentage energy for atrial fibrillation classification. ( 0,704671607160016 )
Int J Neural Syst - Application of empirical mode decomposition (emd) for automated detection of epilepsy using EEG signals. ( 0,695186274132755 )
Comput. Biol. Med. - Noninvasive detection of mechanical prosthetic heart valve disorder. ( 0,691560653289406 )
J Clin Monit Comput - Classification of sleep apnea types using wavelet packet analysis of short-term ECG signals. ( 0,681365383005453 )
J Med Syst - Analysis of infant cry through weighted linear prediction cepstral coefficients and Probabilistic Neural Network. ( 0,678261793004028 )
Med Biol Eng Comput - Predicting termination of paroxysmal atrial fibrillation using empirical mode decomposition of the atrial activity and statistical features of the heart rate variability. ( 0,676936015067435 )
Comput Methods Programs Biomed - Automatic sleep staging using empirical mode decomposition, discrete wavelet transform, time-domain, and nonlinear dynamics features of heart rate variability signals. ( 0,671452211994192 )
J Med Syst - Diagnosis of epilepsy from electroencephalography signals using multilayer perceptron and Elman Artificial Neural Networks and Wavelet Transform. ( 0,669862099202861 )
Med Biol Eng Comput - Voiceless Arabic vowels recognition using facial EMG. ( 0,660977899052395 )
Comput. Biol. Med. - Time series for blind biosignal classification model. ( 0,657811990040298 )
Comput Methods Programs Biomed - Automatic classification of sleep stages based on the time-frequency image of EEG signals. ( 0,655108484718256 )
Methods Inf Med - Classification of sleep stages using multi-wavelet time frequency entropy and LDA. ( 0,655048096605114 )
Int J Neural Syst - Application of quantum-behaved particle swarm optimization to motor imagery EEG classification. ( 0,653891334154509 )
Comput. Biol. Med. - Feature extraction and recognition of ictal EEG using EMD and SVM. ( 0,653866245455652 )
Comput Methods Programs Biomed - Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal. ( 0,651634968916429 )
J Biomed Inform - A framework and its empirical study of automatic diagnosis of traditional Chinese medicine utilizing raw free-text clinical records. ( 0,651578739551679 )
Artif Intell Med - Kernel machines for epilepsy diagnosis via EEG signal classification: a comparative study. ( 0,650719362994547 )
J Med Syst - Automatic and adaptive classification of electroencephalographic signals for brain computer interfaces. ( 0,650226692181116 )
IEEE J Biomed Health Inform - Sleep and wake classification with actigraphy and respiratory effort using dynamic warping. ( 0,64830374580742 )
J Clin Monit Comput - Identification of apnea during respiratory monitoring using support vector machine classifier: a pilot study. ( 0,645792524747806 )
Int J Neural Syst - Comparison of ictal and interictal EEG signals using fractal features. ( 0,645549313616376 )
Med Biol Eng Comput - Signal feature extraction by multi-scale PCA and its application to respiratory sound classification. ( 0,645498131595218 )
Comput. Biol. Med. - Medical decision support system for diagnosis of neuromuscular disorders using DWT and fuzzy support vector machines. ( 0,645494509094373 )
Comput Methods Programs Biomed - Classification of the electrocardiogram signals using supervised classifiers and efficient features. ( 0,643107776173904 )
Int J Comput Assist Radiol Surg - Disc herniation diagnosis in MRI using a CAD framework and a two-level classifier. ( 0,640680013580676 )
Med Biol Eng Comput - SEMG-based hand motion recognition using cumulative residual entropy and extreme learning machine. ( 0,633668270954411 )
Comput Methods Programs Biomed - Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients. ( 0,633485196259631 )
J Med Syst - A biomedical system based on artificial neural network and principal component analysis for diagnosis of the heart valve diseases. ( 0,629746319020765 )
Med Biol Eng Comput - Wavelet-based sparse functional linear model with applications to EEGs seizure detection and epilepsy diagnosis. ( 0,629381702754861 )
Int J Neural Syst - Automated diagnosis of epilepsy using CWT, HOS and texture parameters. ( 0,628114688875364 )
Comput. Biol. Med. - Self-evaluated automatic classifier as a decision-support tool for sleep/wake staging. ( 0,626260357208213 )
Artif Intell Med - Automatic sleep scoring: a search for an optimal combination of measures. ( 0,625746470850013 )
Comput Math Methods Med - The analysis of surface EMG signals with the wavelet-based correlation dimension method. ( 0,62549337504281 )
Int J Med Robot - Smoke detection in endoscopic surgery videos: a first step towards retrieval of semantic events. ( 0,623336857685774 )
J Med Syst - Detection of carotid artery disease by using Learning Vector Quantization Neural Network. ( 0,619979143160222 )
J Med Syst - Application of higher order spectra to identify epileptic EEG. ( 0,616266124628205 )
Comput Methods Programs Biomed - Clustering technique-based least square support vector machine for EEG signal classification. ( 0,615416604758458 )
J Med Syst - A wavelet transform based feature extraction and classification of cardiac disorder. ( 0,613467083804168 )
Int J Neural Syst - Application of higher order cumulant features for cardiac health diagnosis using ECG signals. ( 0,612963384790438 )
Int J Neural Syst - Detection of driving fatigue by using noncontact EMG and ECG signals measurement system. ( 0,607486186424417 )
Comput. Biol. Med. - Wavelet adaptation for automatic voice disorders sorting. ( 0,606623597920101 )
IEEE J Biomed Health Inform - Fall detection based on body part tracking using a depth camera. ( 0,605131244100689 )
Comput. Biol. Med. - Ant colony optimization-based feature selection method for surface electromyography signals classification. ( 0,605056783770534 )
Methods Inf Med - Investigation of an automatic sleep stage classification by means of multiscorer hypnogram. ( 0,604921053545678 )
Comput. Biol. Med. - Automatic classification of infant sleep based on instantaneous frequencies in a single-channel EEG signal. ( 0,604733446886959 )
Comput Methods Programs Biomed - ECG beat classification using a cost sensitive classifier. ( 0,603613653241195 )
IEEE J Biomed Health Inform - Extracting and Selecting Distinctive EEG Features for Efficient Epileptic Seizure Prediction. ( 0,601950019040614 )
J Med Syst - Developing a real time electrocardiogram system using virtual bio-instrumentation. ( 0,5985159795841 )
Comput. Biol. Med. - Wavelet analysis for detection of phasic electromyographic activity in sleep: influence of mother wavelet and dimensionality reduction. ( 0,59809093452204 )
Comput Methods Programs Biomed - Automatic multi-modal intelligent seizure acquisition (MISA) system for detection of motor seizures from electromyographic data and motion data. ( 0,596652229914187 )
Comput Math Methods Med - Analyzing EEG of quasi-brain-death based on dynamic sample entropy measures. ( 0,595957189180544 )
Med Biol Eng Comput - Cross-correlation of EEG frequency bands and heart rate variability for sleep apnoea classification. ( 0,594443563812092 )
Comput Math Methods Med - Knee joint vibration signal analysis with matching pursuit decomposition and dynamic weighted classifier fusion. ( 0,594111121296346 )
Artif Intell Med - Electrocardiogram analysis using a combination of statistical, geometric, and nonlinear heart rate variability features. ( 0,593910357919626 )
Artif Intell Med - Classification of healthy and abnormal swallows based on accelerometry and nasal airflow signals. ( 0,593906345109668 )
J Med Syst - HMM for classification of Parkinson's disease based on the raw gait data. ( 0,593529234050744 )
Comput. Biol. Med. - Odorant recognition using biological responses recorded in olfactory bulb of rats. ( 0,592925919213207 )
J Med Syst - Automatic classification of heartbeats using wavelet neural network. ( 0,592723106420162 )
J Med Syst - Detection and localization of myocardial infarction using K-nearest neighbor classifier. ( 0,590043169082911 )
IEEE J Biomed Health Inform - Comparing supervised learning techniques on the task of physical activity recognition. ( 0,589654401054442 )
J Clin Monit Comput - Heart rate variability analysis during central hypovolemia using wavelet transformation. ( 0,588573476986786 )
Med Biol Eng Comput - Automated detection of obstructive sleep apnoea syndrome from oxygen saturation recordings using linear discriminant analysis. ( 0,58836648438671 )
Int J Health Geogr - Hyperspectral hybrid method classification for detecting altered mucosa of the human larynx. ( 0,588197019271677 )
Med Biol Eng Comput - Optimizing bioimpedance measurement configuration for dual-gated nuclear medicine imaging: a sensitivity study. ( 0,587724769111796 )
Comput Methods Programs Biomed - Feature extraction of the first difference of EMG time series for EMG pattern recognition. ( 0,587605879093276 )
J Med Syst - The quantification of the QT-RR interaction in ECG signal using the detrended fluctuationanalysis and ARARX modelling. ( 0,587399229133137 )
Artif Intell Med - Supervised machine learning-based classification of oral malodor based on the microbiota in saliva samples. ( 0,587369692591015 )
Med Biol Eng Comput - Automatic detection of motion artifacts in the ballistocardiogram measured on a modified bathroom scale. ( 0,587070024482011 )
Comput Math Methods Med - Evaluation of EEG features in decoding individual finger movements from one hand. ( 0,585882472397885 )
Med Biol Eng Comput - Classification of multichannel EEG patterns using parallel hidden Markov models. ( 0,58554942614562 )
Comput. Biol. Med. - Binary symbolic dynamics classifies heart rate variability patterns linked to autonomic modulations. ( 0,58351077278643 )
Comput Methods Programs Biomed - Detection of temporal changes in psychophysiological data using statistical process control methods. ( 0,583441655162058 )
Comput Methods Programs Biomed - An approach based on wavelet analysis for feature extraction in the a-wave of the electroretinogram. ( 0,582891631182996 )
Comput. Biol. Med. - Current methods in electrocardiogram characterization. ( 0,582725450153572 )
J Med Syst - Employment and comparison of different Artificial Neural Networks for epilepsy diagnosis from EEG signals. ( 0,582026328304956 )
Comput. Biol. Med. - Detection of artifacts from high energy bursts in neonatal EEG. ( 0,578578392932169 )
Comput. Biol. Med. - Computer-aided diagnosis system for the Acute Respiratory Distress Syndrome from chest radiographs. ( 0,577579174169676 )
J Med Syst - Automated classification of liver disorders using ultrasound images. ( 0,577221206070816 )
Comput. Biol. Med. - A fixed point algorithm for extracting the atrial activity in the frequency domain. ( 0,576467825956666 )
Artif Intell Med - Differences in examination characteristics of pigmented skin lesions: results of an eye tracking study. ( 0,575966786195989 )
J Biomed Inform - A general framework for time series data mining based on event analysis: application to the medical domains of electroencephalography and stabilometry. ( 0,574531089502856 )
Comput. Biol. Med. - Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders. ( 0,574000687383503 )
Artif Intell Med - Improving the accuracy of suicide attempter classification. ( 0,573953831257318 )
Comput. Biol. Med. - Detection of seizures in EEG using subband nonlinear parameters and genetic algorithm. ( 0,573637614482962 )
Comput Methods Programs Biomed - Prediction of paroxysmal atrial fibrillation based on non-linear analysis and spectrum and bispectrum features of the heart rate variability signal. ( 0,573629671480927 )
Comput. Biol. Med. - Comparison of different EEG features in estimation of hypnosis susceptibility level. ( 0,573598971197887 )
J Med Syst - Classification of arrhythmia using hybrid networks. ( 0,572100669192901 )
Med Biol Eng Comput - ECG signal analysis for the assessment of sleep-disordered breathing and sleep pattern. ( 0,570741925256914 )
J Med Syst - Luminance sticker based facial expression recognition using discrete wavelet transform for physically disabled persons. ( 0,570723770279179 )
Comput Math Methods Med - A novel automatic detection system for ECG arrhythmias using maximum margin clustering with immune evolutionary algorithm. ( 0,570397607989051 )
J Med Syst - A new QRS detection method using wavelets and artificial neural networks. ( 0,570256366451712 )
Comput. Biol. Med. - Estimating cognitive workload using wavelet entropy-based features during an arithmetic task. ( 0,569996238704363 )
Comput Methods Programs Biomed - Spatial fuzzy c-means algorithm with adaptive fuzzy exponent selection for robust vermilion border detection in healthy and diseased lower lips. ( 0,56983754312936 )
Comput Methods Programs Biomed - QRS detection using S-Transform and Shannon energy. ( 0,569327671883501 )
Med Biol Eng Comput - Evaluation of feature extraction methods for EEG-based brain-computer interfaces in terms of robustness to slight changes in electrode locations. ( 0,566404544220196 )
Int J Neural Syst - Extraction of neural control commands using myoelectric pattern recognition: a novel application in adults with cerebral palsy. ( 0,56640202125398 )
Comput. Biol. Med. - Real-time CHF detection from ECG signals using a novel discretization method. ( 0,565436454388769 )
Comput Methods Programs Biomed - Estimation of spatial-temporal gait parameters in level walking based on a single accelerometer: validation on normal subjects by standard gait analysis. ( 0,565044385602694 )
Med Biol Eng Comput - Automated detection of perinatal hypoxia using time-frequency-based heart rate variability features. ( 0,563962519559626 )