Human Computer Interaction / HCI
Hadi Soltanizadeh; Pouria Sharifi; Ali Maleki
Volume 16, Issue 3 , December 2022, , Pages 241-255
Abstract
Losing of voice and larynx is a major problem for people with speech disorders. It creates serious and negative consequences on the quality of individual and group life of these people, especially in working environments. The development of an intelligent system based on electromyogram signals with the ...
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Losing of voice and larynx is a major problem for people with speech disorders. It creates serious and negative consequences on the quality of individual and group life of these people, especially in working environments. The development of an intelligent system based on electromyogram signals with the ability to recognize speech (without using sound) can be a window of hope for people who lost their larynx and voice due to cancer. Although progress and studies in this field are growing in our country and in different languages, but these studies have not been done for the Persian language. In this article, for the first time, recognition of Persian words was done using electromyogram of facial muscles. For this purpose, sEMG signals were collected from eight facial muscles and six volunteers while speaking twelve Persian words. Then, MFL, VAR, DAMV, LTKE, IQR and Cardinality features were extracted from each channel and each window from the signal, and the 432 features from each signal were reduced to 33 features using the PCA principal component analysis method. Finally, in order to recognize twelve Persian words, the features were given to SVM, KNN and RF classifiers. The average classification accuracy was 83.16%, 81.91% and 78.97%, respectively. Our evaluation in this article gives the hope that by using EMG signals it is possible to recognize the limited words of Persian language.
Human Computer Interaction / HCI
Bita Salimi Qadi; Mehdi Golsorkhtabaramiri
Volume 11, Issue 3 , September 2017, , Pages 243-254
Abstract
Wireless body area networks (WBANs) are specific kinds of wireless sensor network which have been widely used in many areas, especially for health monitoring in the areas of health services and healthcare. Among the most important challenges concerning these networks are performance, high throughput ...
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Wireless body area networks (WBANs) are specific kinds of wireless sensor network which have been widely used in many areas, especially for health monitoring in the areas of health services and healthcare. Among the most important challenges concerning these networks are performance, high throughput and increasing network lifespan. One of the possible ways to increase network lifetime is to use energy harvesting possibility. In energy harvesting WBANs, the energy of the sensor nodes does not end, but upon reaching a threshold, the node goes into a power-consuming mode and becomes blocked and does not participate in the network operation until it reaches the required energy. In this paper, an energy-efficient routing protocol for energy harvesting WBANS is proposed. In this protocol, the medical sensor nodes on the patient's body have the ability of energy harvesting while the routing method and transmitter node are used to transfer data from sensor nodes to the sink. This method uses single hob routing when the distance between the sensor node and the sink is less than that of the sensor node to the transmitter node. Also, if emergency data is detected, a single hob routing is used to send data, otherwise, multi hob routing is used to do so. Also, to increase throughput during energy harvesting, the sensor node does not block, but sends the data to its nearest neighbor. This protocol has been able to improve network throughput and lifetime. We used energy harvesting to increase network lifetime and routing techniques to reduce energy consumption.
Human Computer Interaction / HCI
Sahar Sadeghi; Ali Maleki
Volume 11, Issue 2 , June 2017, , Pages 101-109
Abstract
To increase the number of stimulation frequencies in the Steady-state visual evoked potential (SSVEP)-based brain-computer interface, we are forced to broaden the frequency range due to the frequency resolution restriction. This will enter frequencies with harmonic relation into the stimulation frequency ...
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To increase the number of stimulation frequencies in the Steady-state visual evoked potential (SSVEP)-based brain-computer interface, we are forced to broaden the frequency range due to the frequency resolution restriction. This will enter frequencies with harmonic relation into the stimulation frequency range and lead to increase in frequency recognition error. In this paper, a three-stage method including the empirical mode decomposition (EMD), the canonical correlation analysis (CCA) and neural network classifier has been proposed that can solve the recognition error problem for wide frequency range including frequencies with harmonic relation. Visual stimulus ranged from 6-16 Hz with an interval of 0.5 have been generated using Matlab and the psychophysics toolbox. The SSVEP signal was recorded from ten subjects via one electrode placed at Oz. After extracting the intrinsic mode functions (IMFs) of the signal by EMD and reconstructing the combined signals, the CCA has been applied. Two features including the detected frequency and the correlation value in this frequency have been extracted and they were given to the neural network classifier. For eight-second time window, the average accuracy of the CCA for N=1 was 78% and for N=2 was 74%, while the corresponding values of the proposed method were 82% and 77% respectively. For four-second time window, the accuracy was increased from 78% to 83% for N=1 and it was increased from 78% to 80% for N=2. N is the number of harmonics in the generation of the reference signal in the CCA. For wide frequency range, the proposed method has been able to improve the frequency recognition accuracy compared to the standard CCA method. according to this, by broadening the stimulation frequency range, the possibility of increasing the number of frequency options and thus increasing the information transfer rate are provided.
Human Computer Interaction / HCI
Mohsen Keshtkar; Amin Mahnam; Pegah Poladian
Volume 10, Issue 4 , January 2017, , Pages 279-290
Abstract
Steady State Visual Evoked Potentials (SSVEP) have been widely used in development of Brain Computer Interfaces (BCI). However, it is still a research challenge to have visual stimuli which provide strong SSVEP response while produce little eye fatigue. In this study, rectangular, sinosoidal, sawtooth ...
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Steady State Visual Evoked Potentials (SSVEP) have been widely used in development of Brain Computer Interfaces (BCI). However, it is still a research challenge to have visual stimuli which provide strong SSVEP response while produce little eye fatigue. In this study, rectangular, sinosoidal, sawtooth waveforms applied to a LED were compared with sum of two sinusoidals and a frequency modulated waveform to determine the most appropriate visual stimulus for realization of a BCI system. Moreover, circular, ring and anti-phase two rectangular flickers were generated by Cogent toolbox on a laptop screen and compared. Experiments were performed on 12 participants to determine the SSVEP response and eye fatigue corresponding to each of these visual stimuli. Experiments with the waveforms demonstrate that sum of two sine waves generated significantly lower SSVEP amplitude, but the responses for other four waveforms were not significantly different. On the other hand, the frequency modulated waveform resulted in the least eye fatigue significantly lower from other waveforms. Therefore, considering both criteria, frequency modulated waveform can provide superor performance in a BCI system with an average response of 17.3 pV2 and 1.58 fatigue level in a 1-4 fatigue scale. Experiments with visual stimuli on LCD showed that circular stimuli provided highest and anti-phase rectangular the lowest response. But all of them produced high levels of eye fatigue. Although, Circular stimuli had the highest power (26.7pV2) but due to its related high eye fatigue (3.8) it is not recommended for practical applications. In conclusion it is recommended to use frequency modulated visual stimuli for development of practical BCI systems to satisfy both strong response and low eye fatigue criteria.
Rehabilitation Engineering
Diako Mardanbeigi; Mohammad Reza Mallakzadeh
Volume 4, Issue 4 , June 2010, , Pages 267-278
Abstract
This paper investigates prototyping an online, low-cost, video based and applicable eye tracker, which is called "Dias Eye Tracker". Disabled people can use the proposed system to communicate with computer. What have made the system different from the other low-cost eye trackers, are the accuracy of ...
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This paper investigates prototyping an online, low-cost, video based and applicable eye tracker, which is called "Dias Eye Tracker". Disabled people can use the proposed system to communicate with computer. What have made the system different from the other low-cost eye trackers, are the accuracy of gaze estimation, the different application parts of the software and the lightweight wireless hardware, which can be mounted on the user’s head. This paper introduces the software/hardware and the methods of the system. In addition, two methods of pupil tracking have been compared together, and an uncertainty analysis on the mapping function of the system has been done. The performance of the designed eye tracker has been evaluated by analyzing the answers to the three questionnaires, which were filled by disabled people after performing three specific tasks. The results show that the system performs well for interaction with computer.
