| 1. |
- Brown, Shannon, et al.
(författare)
-
Intarsia-sensorized band and textrodes for real-time myoelectric pattern recognition
- 2016
-
Ingår i: Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the. - : Institute of Electrical and Electronics Engineers (IEEE). - 1557-170X. - 9781457702204 ; , s. 6074-6077
-
Konferensbidrag (refereegranskat)abstract
- Surface Electromyography (sEMG) has applications in prosthetics, diagnostics and neuromuscular rehabilitation. Self-adhesive Ag/AgCl are the electrodes preferentially used to capture sEMG in short-term studies, however their long-term application is limited. In this study we designed and evaluated a fully integrated smart textile band with electrical connecting tracks knitted with intarsia techniques and knitted textile electrodes. Real-time myoelectric pattern recognition for motor volition and signal-to-noise ratio (SNR) were used to compare its sensing performance versus the conventional Ag-AgCl electrodes. After a comprehending measurement and performance comparison of the sEMG recordings, no significant differences were found between the textile and the Ag-AgCl electrodes in SNR and prediction accuracy obtained from pattern recognition classifiers.
|
|
| 2. |
- Gu, Irene Yu-Hua, 1953, et al.
(författare)
-
3D Limb Movement Tracking and Analysis for Neurological Dysfunctions of Neonates Using Multi-Camera Videos
- 2016
-
Ingår i: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781457702204 ; 2016-October, s. 2395-2398
-
Konferensbidrag (refereegranskat)abstract
- Central nervous system dysfunction in infants may be manifested through inconsistent, rigid and abnormal limb movements. Detection of limb movement anomalies associated with such neurological dysfunctions in infants is the first step towards early treatment for improving infant development. This paper addresses the issue of detecting and quantifying limb movement anomalies in infants through non-invasive 3D image analysis methods using videos from multiple camera views. We propose a novel scheme for tracking 3D time trajectories of markers on infant’s limbs by video analysis techniques. The proposed scheme employ videos captured from three camera views. This enables us to detect a set of enhanced 3D markers through cross-view matching and to effectively handle marker self-occlusions by other body parts. We track a set of 3D trajectories of limb movements by a set of particle filters in parallel, enabling more robust 3D tracking of markers, and use the 3D model errors for quantifying abrupt limb movements. The proposed work makes a significant advancement to the previous work in [1] through employing tracking in 3D space, and hence overcome several main barriers that hinder real applications by using single camera-based techniques. To the best of our knowledge, applying such a multi-view video analysis approach for assessing neurological dysfunctions of infants through 3D time trajectories of markers on limbs is novel, and could lead to computer-aided tools for diagnosis of dysfunctions where early treatment may improve infant development. Experiments were conducted on multi-view neonate videos recorded in a clinical setting and results have provided further support to the proposed method.
|
|
| 3. |
- Medved, Dennis, et al.
(författare)
-
Selection of an optimal feature set to predict heart transplantation outcomes
- 2016
-
Ingår i: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. - 1557-170X. - 9781457702204 ; 2016-October, s. 3290-3293
-
Konferensbidrag (refereegranskat)abstract
- Heart transplantation (HT) is a life saving procedure, but a limited donor supply forces the surgeons to prioritize the recipients. The understanding of factors that predict mortality could help the doctors with this task. The objective of this study is to find locally optimal feature sets to predict survival of HT patients for different time periods. To this end, we applied logistic regression together with a greedy forward and backward search. As data source, we used the United Network for Organ Sharing (UNOS) registry, where we extracted adult patients (>17 years) from January 1997 to December 2008. As methods to predict survival, we used the Index for Mortality Prediction After Cardiac Transplantation (IMPACT) and the International Heart Transplant Survival Algorithm (IHTSA). We used the LIBLINEAR library together with the Apache Spark cluster computing framework to carry out the computation and we found feature sets for 1, 5, and 10 year survival for which we obtained area under the ROC curves (AUROC) of 68%, 68%, and 76%, respectively.
|
|
| 4. |
|
|
| 5. |
- Abualhoul, Mohammad Y., et al.
(författare)
-
Free space optical link for biomedical applications
- 2012
-
Ingår i: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781424441198 ; , s. 1667-1670
-
Konferensbidrag (refereegranskat)abstract
- Free space optics is an interesting alternative for telemetry with medical implants, due to the high data bandwidths available at optical frequencies. Especially implanted brain-computer interfaces gives rise to large data sets that needs to be transmitted transcutaneous. In this paper we show that it is possible to establish such a link at near-IR wavelengths using a modulated reflector in the implant, thus keeping the laser and the detector on the outside. In addition, we show that it will not only work on short, i.e. touch, distances but also at larger distances, in the range of a meter. We have used an electro absorption modulator to modulate the reflection of an external laser source back towards an external detector. The only part of this system that needs to be implanted is the modulator and drive electronics. The study has been done both by Monte-Carlo simulations of a multi-layer model of a rat skull, and with an experiment demonstrating the feasibility of the link when transmitted through biological tissue. The results show that it is possible to establish a transcutaneous link with an external laser source and light detector, and an internal modulated reflector.
|
|
| 6. |
- Ahkami, Bahareh, 1994, et al.
(författare)
-
Probability-Based Rejection of Decoding Output Improves the Accuracy of Locomotion Detection During Gait
- 2023
-
Ingår i: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X.
-
Konferensbidrag (refereegranskat)abstract
- Prosthetic users need reliable control over their assistive devices to regain autonomy and independence, particularly for locomotion tasks. Despite the potential for myoelectric signals to reflect the users' intentions more accurately than external sensors, current motorized prosthetic legs fail to utilize these signals, thus hindering natural control. A reason for this challenge could be the insufficient accuracy of locomotion detection when using muscle signals in activities outside the laboratory, which may be due to factors such as suboptimal signal recording conditions or inaccurate control algorithms.This study aims to improve the accuracy of detecting locomotion during gait by utilizing classification post-processing techniques such as Linear Discriminant Analysis with rejection thresholds. We utilized a pre-recorded dataset of electromyography, inertial measurement unit sensor, and pressure sensor recordings from 21 able-bodied participants to evaluate our approach. The data was recorded while participants were ambulating between various surfaces, including level ground walking, stairs, and ramps. The results of this study show an average improvement of 3% in accuracy in comparison with using no post-processing (p-value < 0.05). Participants with lower classification accuracy profited more from the algorithm and showed greater improvement, up to 8% in certain cases. This research highlights the potential of classification post-processing methods to enhance the accuracy of locomotion detection for improved prosthetic control algorithms when using electromyogram signals.Clinical Relevance-Decoding of locomotion intent can be improved using post-processing techniques thus resulting in a more reliable control of lower limb prostheses.
|
|
| 7. |
- Alcaraz Martinez, Raul, et al.
(författare)
-
Application of frequency and sample entropy to discriminate long-term recordings of paroxysmal and persistent atrial fibrillation
- 2010
-
Ingår i: Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. - 1557-170X. - 9781424441235 ; , s. 4558-4561
-
Konferensbidrag (refereegranskat)abstract
- Atrial fibrillation (AF) is the most common arrhythmia in clinical practice. At an early stage of the disease, AF may terminate spontaneously and is then referred to as paroxysmal AF. On the other hand, when external intervention is required for the arrhythmia to terminate, it is referred to as persistent AF. In this work, a method to discriminate between paroxysmal and persistent AF in the long-term ECGs is presented. The dominant frequency as well as the organization of the atrial activity are employed to characterize AF. The dominant atrial frequency (DAF) is estimated using hidden Markov model based frequency tracking, and organization is estimated by the sample entropy of the main atrial wave (MAW) and the first two harmonics, respectively. Long-term variations in DAF and organization from 50 ECG recordings were evaluated, showing that episodes of paroxysmal AF were consistently associated with lower DAF and organization of the MAW and the harmonics, than was persistent AF. Discrimination of paroxysmal and persistent AF resulted in classification rates of 84.1±26.1%, thus suggesting that it possible to discriminate between paroxysmal and persistent AF in patients without previously known AF history.
|
|
| 8. |
- Alipoor, Mohammad, 1983, et al.
(författare)
-
On High Order Tensor-based Diffusivity Profile Estimation
- 2013
-
Ingår i: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781457702167 ; , s. 93-96, s. 4-
-
Konferensbidrag (refereegranskat)abstract
- Diffusion weighted magnetic resonance imaging (dMRI) is used to measure, in vivo, the self-diffusion of water molecules in biological tissues. High order tensors (HOTs) are used to model the apparent diffusion coefficient (ADC) profile at each voxel from the dMRI data. In this paper we propose: (i) A new method for estimating HOTs from dMRI data based on weighted least squares (WLS) optimization; and (ii) A new expression for computing the fractional anisotropy from a HOT that does not suffer from singularities and spurious zeros. We also present an empirical evaluation of the proposed method relative to the two existing methods based on both synthetic and real human brain dMRI data. The results show that the proposed method yields more accurate estimation than the competing methods.
|
|
| 9. |
- Anderson, Rachele, et al.
(författare)
-
Insights on Spectral Measures for HRV Based on a Novel Approach for Data Acquisition
- 2018
-
Ingår i: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. - 1557-170X. ; 2018, s. 510-513
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we present new insights on classical spectral measures for heart rate variability (HRV), based on a novel method for HRV acquisition. A dynamic breathing task, where the test participants are asked to breathe following a metronome with slowly increasing frequency, allows for the acquisition of respiratory-related HRV-data covering the frequency range in which adults breathe in different everyday situations. We discuss how the use of a time-frequency representation, e.g. the spectrogram or the Wigner-Ville distribution, should be preferred to the traditional use of the periodogram, due to the non-stationarity of the data. We argue that this approach can highlight the correlation of spectral measures such as low-frequency and high-frequency HRV with relevant factors as age, gender and Body-Mass-Index, thanks to the improved quality of the spectral measures.
|
|
| 10. |
- Behjat, Hamid, et al.
(författare)
-
Canonical cerebellar graph wavelets and their application to fMRI activation mapping
- 2014
-
Ingår i: [Host publication title missing]. - 1557-170X. ; , s. 1039-1042
-
Konferensbidrag (refereegranskat)abstract
- Wavelet-based statistical parametric mapping (WSPM) is an extension of the classical approach in fMRI activation mapping that combines wavelet processing with voxel-wise statistical testing. We recently showed how WSPM, using graph wavelets tailored to the full gray-matter (GM) structure of each individual’s brain, can improve brain activity detection compared to using the classical wavelets that are only suited for the Euclidian grid. However, in order to perform analysis on a subject-invariant graph, canonical graph wavelets should be designed in normalized brain space. We here introduce an approach to define a fixed template graph of the cerebellum, an essential component of the brain, using the SUIT cerebellar template. We construct a corresponding set of canonical cerebellar graph wavelets, and adopt them in the analysis of both synthetic and real data. Compared to classical SPM, WSPM using cerebellar graph wavelets shows superior type-I error control, an empirical higher sensitivity on real data, as well as the potential to capture subtle patterns of cerebellar activity.
|
|
