Try a new search

Format these results:

Searched for:



Total Results:


Signal Processing in Medicine and Biology: Innovations in Big Data Processing

Obeid, Iyad; Picone, Joseph; Selesnick, Ivan
[S.l.] : Springer International Publishing, 2023
Extent: 1 v.
ISBN: 9783031212352
CID: 5501492

Phenomenology Based Decomposition of Sea Clutter with a Secondary Target Classifier

Chapter by: Farshchian, Masoud; Cowen, Benjamin; Selesnick, Ivan
in: Proceedings of the IEEE Radar Conference by
[S.l.] : Institute of Electrical and Electronics Engineers Inc., 2023
pp. ?-?
ISBN: 9781665436694
CID: 5549882

Accuracy of clinical versus oculographic detection of pathological saccadic slowing

Grossman, Scott N; Calix, Rachel; Hudson, Todd; Rizzo, John Ross; Selesnick, Ivan; Frucht, Steven; Galetta, Steven L; Balcer, Laura J; Rucker, Janet C
Saccadic slowing as a component of supranuclear saccadic gaze palsy is an important diagnostic sign in multiple neurologic conditions, including degenerative, inflammatory, genetic, or ischemic lesions affecting brainstem structures responsible for saccadic generation. Little attention has been given to the accuracy with which clinicians correctly identify saccadic slowing. We compared clinician (n = 19) judgements of horizontal and vertical saccade speed on video recordings of saccades (from 9 patients with slow saccades, 3 healthy controls) to objective saccade peak velocity measurements from infrared oculographic recordings. Clinician groups included neurology residents, general neurologists, and fellowship-trained neuro-ophthalmologists. Saccades with normal peak velocities on infrared recordings were correctly identified as normal in 57% (91/171; 171 = 9 videos × 19 clinicians) of clinician decisions; saccades determined to be slow on infrared recordings were correctly identified as slow in 84% (224/266; 266 = 14 videos × 19 clinicians) of clinician decisions. Vertical saccades were correctly identified as slow more often than horizontal saccades (94% versus 74% of decisions). No significant differences were identified between clinician training levels. Reliable differentiation between normal and slow saccades is clinically challenging; clinical performance is most accurate for detection of vertical saccade slowing. Quantitative analysis of saccade peak velocities enhances accurate detection and is likely to be especially useful for detection of mild saccadic slowing.
PMID: 36183516
ISSN: 1878-5883
CID: 5359142

Positive sparse signal denoising: What does a CNN learn

Al-Shabili, Abdullah; Selesnick, Ivan W.
Convolutional neural networks (CNNs) provide impressive empirical success in various tasks; however, their inner workings generally lack interpretability. In this paper, we interpret shallow CNNs that we have trained for the task of positive sparse signal denoising. We identify and analyze common structures among the trained CNNs. We show that the learned CNN denoisers can be interpreted as a nonlinear locally-adaptive thresholding procedure, which is an empirical approximation of the minimum mean square error estimator. Based on our interpretation, we train constrained CNN denoisers and demonstrate no loss in performance despite having fewer trainable parameters. The interpreted CNN denoiser is an instance of a multivariate spline regression model, and a generalization of classical proximal thresholding operators.
ISSN: 1070-9908
CID: 5189762

A Kalman Filter Framework for Simultaneous LTI Filtering and Total Variation Denoising

Kheirati Roonizi, Arman; Selesnick, Ivan W.
This paper proposes a Kalman filter framework for signal denoising that simultaneously utilizes conventional linear time-invariant (LTI) filtering and total variation (TV) denoising. In this approach, the desired signal is considered to be a mixture of two distinct components: a band-limited (e.g., low-frequency component, high-frequency component) signal and a sparse-derivative signal. An iterative Kalman filter/smoother approach is formulated where zero-phase LTI filtering is used to estimate the band-limited signal and TV denoising is used to estimate the sparse-derivative signal.
ISSN: 1053-587x
CID: 5330652


Chapter by: Al-Shabili, Abdullah H.; Xu, Xiaojian; Selesnick, Ivan; Kamilov, Ulugbek S.
in: Proceedings - International Conference on Image Processing, ICIP by
[S.l.] : IEEE Computer Society, 2022
pp. 241-245
ISBN: 9781665496209
CID: 5423792

King-Devick Test Performance and Cognitive Dysfunction after Concussion: A Pilot Eye Movement Study

Gold, Doria M; Rizzo, John-Ross; Lee, Yuen Shan Christine; Childs, Amanda; Hudson, Todd E; Martone, John; Matsuzawa, Yuka K; Fraser, Felicia; Ricker, Joseph H; Dai, Weiwei; Selesnick, Ivan; Balcer, Laura J; Galetta, Steven L; Rucker, Janet C
(1) Background: The King-Devick (KD) rapid number naming test is sensitive for concussion diagnosis, with increased test time from baseline as the outcome measure. Eye tracking during KD performance in concussed individuals shows an association between inter-saccadic interval (ISI) (the time between saccades) prolongation and prolonged testing time. This pilot study retrospectively assesses the relation between ISI prolongation during KD testing and cognitive performance in persistently-symptomatic individuals post-concussion. (2) Results: Fourteen participants (median age 34 years; 6 women) with prior neuropsychological assessment and KD testing with eye tracking were included. KD test times (72.6 ± 20.7 s) and median ISI (379.1 ± 199.1 msec) were prolonged compared to published normative values. Greater ISI prolongation was associated with lower scores for processing speed (WAIS-IV Coding, r = 0.72, p = 0.0017), attention/working memory (Trails Making A, r = -0.65, p = 0.006) (Digit Span Forward, r = 0.57, p = -0.017) (Digit Span Backward, r= -0.55, p = 0.021) (Digit Span Total, r = -0.74, p = 0.001), and executive function (Stroop Color Word Interference, r = -0.8, p = 0.0003). (3) Conclusions: This pilot study provides preliminary evidence suggesting that cognitive dysfunction may be associated with prolonged ISI and KD test times in concussion.
PMID: 34942873
ISSN: 2076-3425
CID: 5092962

Effects of hippocampal interictal discharge timing, duration, and spatial extent on list learning

Leeman-Markowski, Beth; Hardstone, Richard; Lohnas, Lynn; Cowen, Benjamin; Davachi, Lila; Doyle, Werner; Dugan, Patricia; Friedman, Daniel; Liu, Anli; Melloni, Lucia; Selesnick, Ivan; Wang, Binhuan; Meador, Kimford; Devinsky, Orrin
Interictal epileptiform discharges (IEDs) can impair memory. The properties of IEDs most detrimental to memory, however, are undefined. We studied the impact of temporal and spatial characteristics of IEDs on list learning. Subjects completed a memory task during intracranial EEG recordings including hippocampal depth and temporal neocortical subdural electrodes. Subjects viewed a series of objects, and after a distracting task, recalled the objects from the list. The impacts of IED presence, duration, and propagation to neocortex during encoding of individual stimuli were assessed. The effects of IED total number and duration during maintenance and recall periods on delayed recall performance were also determined. The influence of IEDs during recall was further investigated by comparing the likelihood of IEDs preceding correctly recalled items vs. periods of no verbal response. Across 6 subjects, we analyzed 28 hippocampal and 139 lateral temporal contacts. Recall performance was poor, with a median of 17.2% correct responses (range 10.4-21.9%). Interictal epileptiform discharges during encoding, maintenance, and recall did not significantly impact task performance, and there was no significant difference between the likelihood of IEDs during correct recall vs. periods of no response. No significant effects of discharge duration during encoding, maintenance, or recall were observed. Interictal epileptiform discharges with spread to lateral temporal cortex during encoding did not adversely impact recall. A post hoc analysis refining model assumptions indicated a negative impact of IED count during the maintenance period, but otherwise confirmed the above results. Our findings suggest no major effect of hippocampal IEDs on list learning, but study limitations, such as baseline hippocampal dysfunction, should be considered. The impact of IEDs during the maintenance period may be a focus of future research.
PMID: 34416521
ISSN: 1525-5069
CID: 4988992

Detection of normal and slow saccades using implicit piecewise polynomial approximation

Dai, Weiwei; Selesnick, Ivan; Rizzo, John-Ross; Rucker, Janet; Hudson, Todd
The quantitative analysis of saccades in eye movement data unveils information associated with intention, cognition, and health status. Abnormally slow saccades are indicative of neurological disorders and often imply a specific pathological disturbance. However, conventional saccade detection algorithms are not designed to detect slow saccades, and are correspondingly unreliable when saccades are unusually slow. In this article, we propose an algorithm that is effective for the detection of both normal and slow saccades. The proposed algorithm is partly based on modeling saccadic waveforms as piecewise-quadratic signals. The algorithm first decreases noise in acquired eye-tracking data using optimization to minimize a prescribed objective function, then uses velocity thresholding to detect saccades. Using both simulated saccades and real saccades generated by healthy subjects and patients, we evaluate the performance of the proposed algorithm and 10 other detection algorithms. We show the proposed algorithm is more accurate in detecting both normal and slow saccades than other algorithms.
PMID: 34125160
ISSN: 1534-7362
CID: 4924622

How sandbag-able are concussion sideline assessments? A close look at eye movements to uncover strategies

Rizzo, John-Ross; Hudson, Todd E; Martone, John; Dai, Weiwei; Ihionu, Oluchi; Chaudhry, Yash; Selesnick, Ivan; Balcer, Laura J; Galetta, Steven L; Rucker, Janet C
Background: Sideline diagnostic tests for concussion are vulnerable to volitional poor performance ("sandbagging") on baseline assessments, motivated by desire to subvert concussion detection and potential removal from play. We investigated eye movements during sandbagging versus best effort on the King-Devick (KD) test, a rapid automatized naming (RAN) task. Methods: Participants performed KD testing during oculography following instructions to sandbag or give best effort. Results: Twenty healthy participants without concussion history were included (mean age 27 ± 8 years). Sandbagging resulted in longer test times (89.6 ± 39.2 s vs 48.2 ± 8.5 s, p < .001), longer inter-saccadic intervals (459.5 ± 125.4 ms vs 311.2 ± 79.1 ms, p < .001) and greater numbers of saccades (171.4 ± 47 vs 138 ± 24.2, p < .001) and reverse saccades (wrong direction for reading) (21.2% vs 11.3%, p < .001). Sandbagging was detectable using a logistic model with KD times as the only predictor, though more robustly detectable using eye movement metrics. Conclusions: KD sandbagging results in eye movement differences that are detectable by eye movement recordings and suggest an invalid test score. Objective eye movement recording during the KD test shows promise for distinguishing between best effort and post-injury performance, as well as for identifying sandbagging red flags.
PMID: 33529094
ISSN: 1362-301x
CID: 4776222