The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
Andrzej Borzecki - One of the best experts on this subject based on the ideXlab platform.
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influence of fenpropathrin on memory and Movement in mice after transient incomplete cerebral ischemia
Journal of Toxicology and Environmental Health, 2010Co-Authors: Barbara Nieradkoiwanicka, Andrzej BorzeckiAbstract:Fenpropathrin, a synthetic pyrethroid widely used as an insecticide, is known to affect locomotion and memory in mammals. It is possible that exposure to pyrethroids may occur in an elderly population where transient ischemic attacks are a higher risk for occurrence with consequent changes in memory and control of Movement. Thus, the aim of this study was to determine whether bilateral clamping of carotid arteries (BCCA), a model for ischemia, together with fenpropathrin affected memory in tests such as the passive avoidance task and fresh spatial memory in a Y-maze, as well as Movement Activity and Movement coordination on a rotarod in mice. BCCA together with fenpropathrin significantly reduced latency in a passive avoidance task compared to controls. There were no significant differences among the groups with respect to the Y-maze, Movement Activity, or Movement coordination. In conclusion, fenpropathrin needs to be used with caution in the presence of an elderly population at risk for ischemia, as the...
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Effect of bifenthrin on memory processes, Movement Activity, and coordination in mice exposed to transient cerebral oligaemia
Bulletin of The Veterinary Institute in Pulawy, 2008Co-Authors: B Nieradko-iwanicka, Andrzej BorzeckiAbstract:The purpose of the present study was to examine whether the effects of exposure to 0.1LD50 of bifenthrin on memory processes, Movement Activity, and coordination could be exacerbated by transient reduction of cerebral oxygen supply. The transient occlusion of both common carotid arteries (BCCA) in adult mice was performed under anaesthesia. Intraperitoneal LD50 for bifethrin was estimated to be 16.1mg/kg b.w. The memory retention was evaluated in a step-through passive avoidance task (PA), working spatial memory in a Y-maze, Movement coordination on a rota-rod, and Movement Activity in an automated device. Long-term memory impairment caused by bifenthrin was exacerbated by BCCA. Movement co-ordination was significantly altered in animals treated with the compound. Movement Activity was slightly decreased in animals after BCCA and pesticide injection. These results indicate that cerebral oligaemic hypoxia potentiates long-term memory impairing effect of bifenthrin.
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Effect of cypermethrin on memory, Movement Activity and co-ordination in mice after transient incomplete cerebral ischemia
Pharmacological reports : PR, 2008Co-Authors: B Nieradko-iwanicka, Andrzej BorzeckiAbstract:Cypermethrin is a synthetic pyrethroid widely used as an insecticide. The aim of the present study was to investigate the possible effect of 0.1 LD50 of cypermethrin on memory, Movement Activity and co-ordination in mice exposed to transient incomplete cerebral ischemia. Transient occlusion of both carotid arteries (BCCA) in adult female mice was performed under ketamine + xylazine anesthesia. Intraperitoneal LD50 for cypermethrin was calculated to be 169.9 mg/kg. Memory retention was evaluated in a step-through passive avoidance task (PA), working spatial memory in a Y-maze, spontaneous Movement Activity in an automated device fitted with two photocells and a counter in two subsequent 30-min periods, and Movement co-ordination on a rod spinning at the rate of 10 rotations/min. Neither memory nor Movement co-ordination were significantly affected by transient incomplete cerebral ischemia or cypermethrin. BCCA itself did not impair Movement Activity in the examined mice. Cypermethrin decreased exploratory motor Activity in the mice, and the effect was exacerbated by BCCA. These results show that transient incomplete cerebral ischemia combined with exposure to subtoxic doses of cypermethrin do not impair memory, but do affect behavior, producing transient reduction of spontaneous horizontal Movement in mice.
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INFLUENCE OF SUBTOXIC DOSES OF FENITROTHION ON MEMORY PROCESSES, Movement Activity, AND Movement COORDINATION IN MICE EXPOSED TO TRANSIENT OLIGAEMIC BRAIN HYPOXIA
Bulletin of The Veterinary Institute in Pulawy, 2008Co-Authors: B Nieradko-iwanicka, Andrzej BorzeckiAbstract:The aim of the study was to find out if subtoxic doses of fenitrothion (0.1 LD50, LD50 =166.6 mg/kg) administered to mice exposed to transient oligaemic brain hypoxia induced by bilateral clamping of the carotid arteries (BCCA) influence memory processes, Movement Activity, and coordination. The BCCA was carried out under ketamine + xylazine anaesthesia. Common carotid arteries were clamped for 30 min. Twenty-four hours later; the animals were injected intraperitoneally with 0.1 LD50 of fenitrothion. Controls and sham-operated animals (with carotids separated but not clamped) were injected with respective volumes of bidistilled water. All the animals were trained in passive avoidance (PA) task. The examination of memory retention in PA was done 24 h later followed by testing of fresh spatial memory in a Ymaze, Movement co-ordination, and spontaneous Movement Activity in a 30-min period. Fenitrothion did not significantly alter memory processes in the examined mice. However, the Movement coordination was significantly impaired in animals that underwent BCCA alone as well as being oligaemic and under the influence of fenitrothion vs control groups. The same groups demonstrated significantly impaired spontaneous Movement Activity vs controls.
Siddhartha P. Duttagupta - One of the best experts on this subject based on the ideXlab platform.
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Body Movement Activity Recognition for Ambulatory Cardiac Monitoring
IEEE Transactions on Biomedical Engineering, 2007Co-Authors: Tanmay Pawar, Subhasis Chaudhuri, Siddhartha P. DuttaguptaAbstract:Wearable electrocardiogram (W-ECG) recorders are increasingly in use by people suffering from cardiac abnormalities who also choose to lead an active lifestyle. The challenge presently is that the ECG signal is influenced by motion artifacts induced by body Movement Activity (BMA) of the wearer. The usual practice is to develop effective filtering algorithms which will eliminate artifacts. Instead, our goal is to detect the motion artifacts and classify the type of BMA from the ECG signal itself. We have recorded the ECG signals during specified BMAs, e.g., sitting still, walking, Movements of arms and climbing stairs, etc. with a single-lead system. The collected ECG signal during BMA is presumed to be an additive mix of signals due to cardiac activities, motion artifacts and sensor noise. A particular class of BMA is characterized by applying eigen decomposition on the corresponding ECG data. The classification accuracies range from 70% to 98% for various class combinations of BMAs depending on their uniqueness based on this technique. The above classification is also useful for analysis of P and T waves in the presence of BMA
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Transition Detection in Body Movement Activities for Wearable ECG
IEEE Transactions on Biomedical Engineering, 2007Co-Authors: Tanmay D. Pawar, Subhasis Chaudhuri, N.s. Anantakrishnan, Siddhartha P. DuttaguptaAbstract:It has been shown by Pawar (2007) that the motion artifacts induced by body Movement Activity (BMA) in a single-lead wearable electrocardiogram (ECG) signal recorder, while monitoring an ambulatory patient, can be detected and removed by using a principal component analysis (PCA)-based classification technique. However, this requires the ECG signal to be temporally segmented so that each segment comprises of artifacts due to a single type of body Movement Activity. In this paper, we propose a simple, recursively updated PCA-based technique to detect transitions wherever the type of body Movement is changed
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Transition detection in body Movement activities for wearable ECG.
IEEE transactions on bio-medical engineering, 2007Co-Authors: Tanmay Pawar, Subhasis Chaudhuri, N.s. Anantakrishnan, Siddhartha P. DuttaguptaAbstract:It has been shown by Pawar et al. (2007) that the motion artifacts induced by body Movement Activity (BMA) in a single-lead wearable electrocardiogram (ECG) signal recorder, while monitoring an ambulatory patient, can be detected and removed by using a principal component analysis (PCA)-based classification technique. However, this requires the ECG signal to be temporally segmented so that each segment comprises of artifacts due to a single type of body Movement Activity. In this paper, we propose a simple, recursively updated PCA-based technique to detect transitions wherever the type of body Movement is changed.
Jungpil Shin - One of the best experts on this subject based on the ideXlab platform.
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Hand Movement Activity-Based Character Input System on a Virtual Keyboard
Electronics, 2020Co-Authors: Abdur Rahim, Jungpil ShinAbstract:Nowadays, gesture-based technology is revolutionizing the world and lifestyles, and the users are comfortable and care about their needs, for example, in communication, information security, the convenience of day-to-day operations and so forth. In this case, hand Movement information provides an alternative way for users to interact with people, machines or robots. Therefore, this paper presents a character input system using a virtual keyboard based on the analysis of hand Movements. We analyzed the signals of the accelerometer, gyroscope, and electromyography (EMG) for Movement Activity. We explored potential features of removing noise from input signals through the wavelet denoising technique. The envelope spectrum is used for the analysis of the accelerometer and gyroscope and cepstrum for the EMG signal. Furthermore, the support vector machine (SVM) is used to train and detect the signal to perform character input. In order to validate the proposed model, signal information is obtained from predefined gestures, that is, “double-tap”, “hold-fist”, “wave-left”, “wave-right” and “spread-finger” of different respondents for different input actions such as “input a character”, “change character”, “delete a character”, “line break”, “space character”. The experimental results show the superiority of hand gesture recognition and accuracy of character input compared to state-of-the-art systems.
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Arm Movement Activity based user authentication in P2P systems
Peer-to-Peer Networking and Applications, 2019Co-Authors: Jungpil Shin, Md. Rashedul Islam, Md. Abdur Rahim, Hyung-jin MunAbstract:User authentication has become an essential security element that enables a wide range of applications in P2P systems for higher security and safety requirements. In previous, many researchers worked on user authentication based on certificates, passwords, and feature-based authentication (e.g. face recognition, fingerprint detection, iris recognition, voice recognition). However, authentication using those technologies may fail because this information can be easily shared among users or synthesized. Also, there are several cyber and cryptography attacks. With the progress of the latest sensor technology, wearable as Microsoft Bands, Fitbit, and Garmin has provided for more information collecting opportunities. From those above point of views, this paper presents a novel user identification system based on the bio signal analysis of arm Movement (3-axis accelerometer & 3-axis gyroscope) and electromyography (EMG) signal using Myo armband as a wearable user authentication system in P2P system that identifies users based on the bio-signal of Movement of a person’s arm. In this study, the gesture and EMG signals are obtained from the sensor and denoised using wavelet denoising algorithm. The denoised signals are analyzed using the envelope and cepstrum analysis for extracting the potential feature vector. Finally, the feature vector is used to train and identify a user using multi-class support vector machine (MC-SVM) with different kernel function for user authentication. For validating the proposed authentication model, signals are obtained from the arm Movements, i.e., directions and hand gesture data using acceleration, gyroscope and EMG sensors of several subjects. According to the experimental results, the proposed model shows satisfactory performance. To evaluate the efficiency of the proposed systems, we measure and compare its classification accuracy with state-of-the-art algorithms. And the proposed algorithm outperforms with others.
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Arm Movement Activity based user authentication in P2P systems
Peer-to-Peer Networking and Applications, 2019Co-Authors: Jungpil Shin, Md. Rashedul Islam, Md. Abdur Rahim, Hyung-jin MunAbstract:User authentication has become an essential security element that enables a wide range of applications in P2P systems for higher security and safety requirements. In previous, many researchers worked on user authentication based on certificates, passwords, and feature-based authentication (e.g. face recognition, fingerprint detection, iris recognition, voice recognition). However, authentication using those technologies may fail because this information can be easily shared among users or synthesized. Also, there are several cyber and cryptography attacks. With the progress of the latest sensor technology, wearable as Microsoft Bands, Fitbit, and Garmin has provided for more information collecting opportunities. From those above point of views, this paper presents a novel user identification system based on the bio signal analysis of arm Movement (3-axis accelerometer & 3-axis gyroscope) and electromyography (EMG) signal using Myo armband as a wearable user authentication system in P2P system that identifies users based on the bio-signal of Movement of a person’s arm. In this study, the gesture and EMG signals are obtained from the sensor and denoised using wavelet denoising algorithm. The denoised signals are analyzed using the envelope and cepstrum analysis for extracting the potential feature vector. Finally, the feature vector is used to train and identify a user using multi-class support vector machine (MC-SVM) with different kernel function for user authentication. For validating the proposed authentication model, signals are obtained from the arm Movements, i.e., directions and hand gesture data using acceleration, gyroscope and EMG sensors of several subjects. According to the experimental results, the proposed model shows satisfactory performance. To evaluate the efficiency of the proposed systems, we measure and compare its classification accuracy with state-of-the-art algorithms. And the proposed algorithm outperforms with others.
B Nieradko-iwanicka - One of the best experts on this subject based on the ideXlab platform.
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Effect of bifenthrin on memory processes, Movement Activity, and coordination in mice exposed to transient cerebral oligaemia
Bulletin of The Veterinary Institute in Pulawy, 2008Co-Authors: B Nieradko-iwanicka, Andrzej BorzeckiAbstract:The purpose of the present study was to examine whether the effects of exposure to 0.1LD50 of bifenthrin on memory processes, Movement Activity, and coordination could be exacerbated by transient reduction of cerebral oxygen supply. The transient occlusion of both common carotid arteries (BCCA) in adult mice was performed under anaesthesia. Intraperitoneal LD50 for bifethrin was estimated to be 16.1mg/kg b.w. The memory retention was evaluated in a step-through passive avoidance task (PA), working spatial memory in a Y-maze, Movement coordination on a rota-rod, and Movement Activity in an automated device. Long-term memory impairment caused by bifenthrin was exacerbated by BCCA. Movement co-ordination was significantly altered in animals treated with the compound. Movement Activity was slightly decreased in animals after BCCA and pesticide injection. These results indicate that cerebral oligaemic hypoxia potentiates long-term memory impairing effect of bifenthrin.
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Effect of cypermethrin on memory, Movement Activity and co-ordination in mice after transient incomplete cerebral ischemia
Pharmacological reports : PR, 2008Co-Authors: B Nieradko-iwanicka, Andrzej BorzeckiAbstract:Cypermethrin is a synthetic pyrethroid widely used as an insecticide. The aim of the present study was to investigate the possible effect of 0.1 LD50 of cypermethrin on memory, Movement Activity and co-ordination in mice exposed to transient incomplete cerebral ischemia. Transient occlusion of both carotid arteries (BCCA) in adult female mice was performed under ketamine + xylazine anesthesia. Intraperitoneal LD50 for cypermethrin was calculated to be 169.9 mg/kg. Memory retention was evaluated in a step-through passive avoidance task (PA), working spatial memory in a Y-maze, spontaneous Movement Activity in an automated device fitted with two photocells and a counter in two subsequent 30-min periods, and Movement co-ordination on a rod spinning at the rate of 10 rotations/min. Neither memory nor Movement co-ordination were significantly affected by transient incomplete cerebral ischemia or cypermethrin. BCCA itself did not impair Movement Activity in the examined mice. Cypermethrin decreased exploratory motor Activity in the mice, and the effect was exacerbated by BCCA. These results show that transient incomplete cerebral ischemia combined with exposure to subtoxic doses of cypermethrin do not impair memory, but do affect behavior, producing transient reduction of spontaneous horizontal Movement in mice.
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INFLUENCE OF SUBTOXIC DOSES OF FENITROTHION ON MEMORY PROCESSES, Movement Activity, AND Movement COORDINATION IN MICE EXPOSED TO TRANSIENT OLIGAEMIC BRAIN HYPOXIA
Bulletin of The Veterinary Institute in Pulawy, 2008Co-Authors: B Nieradko-iwanicka, Andrzej BorzeckiAbstract:The aim of the study was to find out if subtoxic doses of fenitrothion (0.1 LD50, LD50 =166.6 mg/kg) administered to mice exposed to transient oligaemic brain hypoxia induced by bilateral clamping of the carotid arteries (BCCA) influence memory processes, Movement Activity, and coordination. The BCCA was carried out under ketamine + xylazine anaesthesia. Common carotid arteries were clamped for 30 min. Twenty-four hours later; the animals were injected intraperitoneally with 0.1 LD50 of fenitrothion. Controls and sham-operated animals (with carotids separated but not clamped) were injected with respective volumes of bidistilled water. All the animals were trained in passive avoidance (PA) task. The examination of memory retention in PA was done 24 h later followed by testing of fresh spatial memory in a Ymaze, Movement co-ordination, and spontaneous Movement Activity in a 30-min period. Fenitrothion did not significantly alter memory processes in the examined mice. However, the Movement coordination was significantly impaired in animals that underwent BCCA alone as well as being oligaemic and under the influence of fenitrothion vs control groups. The same groups demonstrated significantly impaired spontaneous Movement Activity vs controls.
Subhasis Chaudhuri - One of the best experts on this subject based on the ideXlab platform.
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Body Movement Activity Recognition for Ambulatory Cardiac Monitoring
IEEE Transactions on Biomedical Engineering, 2007Co-Authors: Tanmay Pawar, Subhasis Chaudhuri, Siddhartha P. DuttaguptaAbstract:Wearable electrocardiogram (W-ECG) recorders are increasingly in use by people suffering from cardiac abnormalities who also choose to lead an active lifestyle. The challenge presently is that the ECG signal is influenced by motion artifacts induced by body Movement Activity (BMA) of the wearer. The usual practice is to develop effective filtering algorithms which will eliminate artifacts. Instead, our goal is to detect the motion artifacts and classify the type of BMA from the ECG signal itself. We have recorded the ECG signals during specified BMAs, e.g., sitting still, walking, Movements of arms and climbing stairs, etc. with a single-lead system. The collected ECG signal during BMA is presumed to be an additive mix of signals due to cardiac activities, motion artifacts and sensor noise. A particular class of BMA is characterized by applying eigen decomposition on the corresponding ECG data. The classification accuracies range from 70% to 98% for various class combinations of BMAs depending on their uniqueness based on this technique. The above classification is also useful for analysis of P and T waves in the presence of BMA
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Transition Detection in Body Movement Activities for Wearable ECG
IEEE Transactions on Biomedical Engineering, 2007Co-Authors: Tanmay D. Pawar, Subhasis Chaudhuri, N.s. Anantakrishnan, Siddhartha P. DuttaguptaAbstract:It has been shown by Pawar (2007) that the motion artifacts induced by body Movement Activity (BMA) in a single-lead wearable electrocardiogram (ECG) signal recorder, while monitoring an ambulatory patient, can be detected and removed by using a principal component analysis (PCA)-based classification technique. However, this requires the ECG signal to be temporally segmented so that each segment comprises of artifacts due to a single type of body Movement Activity. In this paper, we propose a simple, recursively updated PCA-based technique to detect transitions wherever the type of body Movement is changed
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Transition detection in body Movement activities for wearable ECG.
IEEE transactions on bio-medical engineering, 2007Co-Authors: Tanmay Pawar, Subhasis Chaudhuri, N.s. Anantakrishnan, Siddhartha P. DuttaguptaAbstract:It has been shown by Pawar et al. (2007) that the motion artifacts induced by body Movement Activity (BMA) in a single-lead wearable electrocardiogram (ECG) signal recorder, while monitoring an ambulatory patient, can be detected and removed by using a principal component analysis (PCA)-based classification technique. However, this requires the ECG signal to be temporally segmented so that each segment comprises of artifacts due to a single type of body Movement Activity. In this paper, we propose a simple, recursively updated PCA-based technique to detect transitions wherever the type of body Movement is changed.