Anas Imtiaz

Anas Imtiaz
Imperial College London | Imperial · Department of Electrical and Electronic Engineering

PhD

About

33
Publications
10,011
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622
Citations
Additional affiliations
April 2011 - December 2015
Imperial College London
Position
  • Research Assistant

Publications

Publications (33)
Article
Objective: Long-term monitoring of epilepsy patients outside of hospital settings is impractical due to the complexity and costs associated with electroencephalogram (EEG) systems. Alternative sensing modalities that can acquire, and automatically interpret signals through easy-to-use wearable devices, are needed to help with at-home management of...
Article
Full-text available
Objectives Obstructive sleep apnoea (OSA) is a heavily underdiagnosed condition, which can lead to significant multimorbidity. Underdiagnosis is often secondary to limitations in existing diagnostic methods. We conducted a diagnostic accuracy and usability study, to evaluate the efficacy of a novel, low-cost, small, wearable medical device, AcuPebb...
Conference Paper
Electroencephalogram (EEG) is a crucial tool in the diagnosis and management of epilepsy. The process of analyzing EEG is time consuming leading to the development of seizure detection algorithms to aid its analysis. This approach is limited since it requires seizures to occur during monitoring periods and can often lead to misdiagnosis in cases wh...
Article
Full-text available
Designing wearable systems for sleep detection and staging is extremely challenging due to the numerous constraints associated with sensing, usability, accuracy, and regulatory requirements. Several researchers have explored the use of signals from a subset of sensors that are used in polysomnography (PSG), whereas others have demonstrated the feas...
Article
Full-text available
This paper introduces the concept of using acoustic sensing over the radial artery to extract cardiac parameters for continuous vital sign monitoring. It proposes a novel measurement principle that allows detection of the heart sounds together with the pulse wave, an attribute not possible with existing photoplethysmography (PPG)-based methods for...
Article
Wearable devices have seen tremendous growth during the last ten years. This has been made possible with ever-shrinking electronics, cost reductions, and the rise in mobile computing, making it possible to share significant computational workloads. Recent estimates show an annual growth of 17% in wearable devices in 2017, with more than 300 million...
Article
Full-text available
Epilepsy is one of the most common serious brain disorders affecting 1% of the world population. Epileptic seizure events are caused by abnormal excessive neuronal activity in the brain, which may be associated with behavioural changes that severely affect the patients’ quality of life. These events are manifested as abnormal activity in electroenc...
Conference Paper
This paper evaluates the use of breath sound recordings to automatically determine the respiratory health status of a subject. A number of features were investigated and Wilcoxon Rank Sum statistical test was used to determine the significance of the extracted features. The significant features were then passed to a feature selection algorithm base...
Conference Paper
Cough is a common symptom of numerous respiratory diseases. In certain cases, such as asthma and COPD, early identification of coughs is useful for the management of these diseases. This paper presents an algorithm for automatic identification of cough events from acoustic signals. The algorithm is based on only four features of the acoustic signal...
Conference Paper
Monitoring of wheezes is an integral part of managing Chronic Respiratory Diseases such as asthma and Chronic Obstructive Pulmonary Disease (COPD). Recently, there is a growing interest in automatic detection of wheezes and the use of Mel-Frequency Cepstral Coefficients (MFCC) have been shown to achieve encouraging detection performance. While the...
Conference Paper
Cough is a common symptom that manifests in numerous respiratory diseases. In chronic respiratory diseases, such as asthma and COPD, monitoring of cough is an integral part in managing the disease. This paper presents an algorithm for automatic detection of cough events from acoustic signals. The algorithm uses only three spectral features with a l...
Article
Full-text available
Long-term monitoring of epilepsy patients require low-power systems that can record and transmit electroencephalogram data over extended periods of time. Since seizure events are rare, long-term monitoring inherently results in large amounts of data that are recorded and hence need to be reduced. This paper presents an ultra-low power integrated ci...
Article
Full-text available
Chronic Respiratory Diseases (CRDs), such as Asthma and Chronic Obstructive Pulmonary Disease (COPD), are leading causes of deaths worldwide. Although both Asthma and COPD are not curable, they can be managed by close monitoring of symptoms to prevent worsening of the condition. One key symptom that needs to be monitored is the occurrence of wheezi...
Article
Cardiovascular diseases currently pose the highest threat to human health around the world. Proper investigation of the abnormalities in heart sounds is known to provide vital clinical information that can assist in the diagnosis and management of cardiac conditions. However, despite significant advances in the development of algorithms for automat...
Conference Paper
This paper presents a comparison between finger and neck photoplethysmography (PPG) in order to assess the potential and limitations of this, non-conventionally used, body site for application in pulse oximetry. PPG signals were recorded at both sites from healthy subjects to inspect the differences in average waveforms, as well as in oxygen satura...
Article
Full-text available
Heart rate is an important physiological parameter to assess the cardiac condition of an individual and is traditionally determined by attaching multiple electrodes on the chest of a subject to record the electrical activity of the heart. The installation and handling complexities of such systems does not prove feasible for a user to undergo a long...
Article
Full-text available
Understanding brain function at the cell and circuit level requires representation of neuronal activity through multiple recording sites and at high sampling rates. Traditional tethered recording systems restrict movement and limit the environments suitable for testing, while existing wireless technology is still too heavy for extended recording in...
Conference Paper
Oxygen saturation levels are routinely monitored in clinical settings. Pulse oximetry, in transmittance operation mode, is the most common method of estimating oxygen saturation (SpO2). This is inexpensive and non-invasive and thus allows for long-term monitoring. However, it suffers from issues such as signal integrity, reliability and patient com...
Conference Paper
Smoking is a cause of multiple health problems resulting in diseases which can also be fatal. It is well known that smoking has long-term impact on the health of an individual as well. While a number of studies have looked at the impact of smoking on health and its economic impacts, most of these rely on input from smokers in the form of questionna...
Article
This paper presents an ultralow power system on chip (SoC) for automatic sleep staging using a single electroencephalogram (EEG) channel. The system integrates an analog front end for EEG data acquisition and a digital processor to extract spectral features from these data and classify them into one of the sleep stages. The digital processor consis...
Article
Full-text available
Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare f...
Article
Continuous patient monitoring systems acquire enormous amounts of data that is either manually analysed by doctors or automatically processed using intelligent algorithms. Sections of data acquired over long period of time can be corrupted with artefacts due to patient movement, sensor placement and interference from other sources. Owing to the lar...
Conference Paper
Lack of proper restorative sleep can induce sleepiness at odd hours making a person drowsy. This onset of drowsiness can be detrimental for the individual in a number of ways if it happens at an unwanted time. For example, drowsiness while driving a vehicle or operating heavy machinery poses a threat to the safety and wellbeing of individuals as we...
Conference Paper
PhysioNet Sleep EDF database has been the most popular source of data used for developing and testing many automatic sleep staging algorithms. However, the recordings from this database has been used in an inconsistent fashion. For example, arbitrary selection of start and end times from long term recordings, data-hypnogram mismatches, different pe...
Conference Paper
Automatic sleep staging from a reduced number of channels is desirable to save time, reduce costs and make sleep monitoring more accessible by providing home-based polysomnography. This paper introduces a novel algorithm for automatic scoring of sleep stages using a combination of small decision trees driven by a state machine. The algorithm uses t...
Article
Full-text available
Phonocardiography is a widely used method of listening to the heart sounds and indicating the presence of cardiac abnormalities. Each heart cycle consists of two major sounds - S1 and S2 - that can be used to determine the heart rate. The conventional method of acoustic signal acquisition involves placing the sound sensor at the chest where this so...
Article
Full-text available
Sleep spindles are transient waveforms observed on the electroencephalogram (EEG) during the N2 stage of sleep. In this paper we evaluate the use of line length, an efficient and low-complexity time domain feature, for automatic detection of sleep spindles. We use this feature with a simple algorithm to detect spindles achieving sensitivity of 83.6...
Conference Paper
Full-text available
Sleep spindles are the hallmark of N2 stage of sleep. They are transient waveforms observed on sleep electroencephalogram and their identification is required for sleep staging. Due to the large number of sleep spindles appearing on an overnight sleep EEG, automating the detection of sleep spindles would be desirable, not only to save specialist ti...
Article
Full-text available
Seizure detection algorithms have been developed to solve specific problems, such as seizure onset detection, occurrence detection, termination detection and data selection. It is thus inherent that each type of seizure detection algorithm would detect a different EEG characteristic (feature). However most feature comparison studies do not specify...

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