Hussein Al Osman

University of Ottawa · School of Electrical Engineering and Computer Science

Many factors render multimodal affect recognition approaches appealing. First, humans employ a multimodal approach in emotion recognition. It is only fitting that machines, which attempt to reproduce elements of the human emotional intelligence, employ the same approach. Second, the combination of multiple-affective signals not only provides a rich...

Serious games augment utilitarian applications with an entertainment dimension. Hence, information pertaining to a utilitarian objective is seamlessly incorporated into the gaming scenario. In this work, we present the concept of Ubiquitous Biofeedback Serious Games (UBSGs), a family of games that integrate biofeedback processes in their operation....

Touch plays a prominent role in communicating emotions and intensifying interpersonal communication. Affective Haptics is an emerging field, which focuses on the analysis, design, and evaluation of systems that can capture, process, or display emotions via the sense of touch. The objective of this paper is to present an overview of the recent achie...

Gaming on demand is an emerging service that has recently started to garner prominence in the gaming industry. Cloud based video games provide affordable, flexible and high performance solution for end-users with constrained computing resources and enables them to play high-end graphic games on low-end thin clients. Despite its advantages, cloud ga...

Cloud gaming is an emerging service that has recently started to garner prominence in the gaming industry. Since the significant part of computational processing, including game rendering and video compression, is performed in data centers, controlling the transfer of information within the cloud has an important impact on the quality of cloud gami...

Suicidal ideation detection is a vital research area that holds great potential for improving mental health support systems. However, the sensitivity surrounding suicide-related data poses challenges in accessing large-scale, annotated datasets necessary for training effective machine learning models. To address this limitation, we introduce an inn...

Cannabis has become the most used drug worldwide with the highest risks and associated criminal problems in many countries. Therefore, identifying users at risk of cannabis use is an important and essential task. This will help doctors and people with authority to react fast and on time. We used two datasets (8,725 users in total) to build a strong...

Psychotic disorders pose a significant public health concern, and early detection of relapse is a crucial aspect of their management. In this study, we investigate the effectiveness of unsupervised learning-based anomaly detection approaches for relapse detection in psychotic disorders, using data from wearable sensors as a proposed solution for th...

This paper presents a novel framework for quantitatively evaluating the interactive ChatGPT model in the context of suicidality assessment from social media posts, utilizing the University of Maryland Reddit suicidality dataset. We conduct a technical evaluation of ChatGPT's performance on this task using Zero-Shot and Few-Shot experiments and comp...

Relapse detection is a crucial component of mental disorders treatment and management. In this paper, we present our solution for the ICASSP Signal Processing Grand Challenge e-Prevention track 2 Relapse Detection. We propose an unsupervised learning approach to detect relapse in patients with mental health disorders using anomaly detection with an...

This paper presents a novel framework for quantitatively evaluating the interactive ChatGPT model in the context of suicidality assessment from social media posts, utilizing the University of Maryland Reddit suicidality dataset. We conduct a technical evaluation of ChatGPT’s performance on this task using Zero-Shot and Few-Shot experiments and comp...

Cannabis is the most used drug around the world with the highest risks and associated criminal problems in many countries. This research describes the process of classifying online posts to identify cannabis use problems and their associated risks as early as possible. We annotated 11,008 online posts, which we used to build robust classification m...

The limited size of existing datasets and signal variability have hindered EEG-based emotion recognition. In this paper, we present a solution that simultaneously addresses both problems. Generative Adversarial Networks (GANs) have recently shown notable data augmentation (DA) success. Therefore, we leverage a GAN-based DA technique to enhance the...

This letter presents a transducer network framework that supports the amalgamation of multiple transducers into single wireless nodes. This approach is aimed at decreasing energy consumption by reducing the number of wireless transceivers involved in such networks. To make wireless nodes easily reconfigurable, a plug and play mechanism is applied t...

Human stress detection is of great importance for monitoring mental health. The Multimodal Sentiment Analysis Challenge (MuSe) 2021 focuses on emotion, physiological-emotion, and stress recognition as well as sentiment classification by exploiting several modalities. In this paper, we present our solution for the Muse-Stress sub-challenge. The targ...

Recent advances in machine learning have led to a surge of interest in classification of the auditory brainstem response. By conducting a search in the PubMed, Google Scholar, SpringerLink, ScienceDirect, and Scopus databases, it was possible to identify twelve studies that explored the use of machine learning to classify the auditory brainstem res...

Our augmented reality online assistance platform enables an expert to specify 6DoF movements of a component and apply the geometrical and physical constraints in real-time. We track the real components on the expert’s side to monitor the operations of an expert. We leverage a remote rendering technique that we proposed previously to relieve the ren...

In spite of the advent of Machine Learning (ML) and its successful deployment in measurement systems, little information can be found in the literature about uncertainty quantification in these systems [1]. Uncertainty is crucial for the adoption of ML in commercial products and services. Designers are now being encouraged to be upfront about the u...

Like any science and engineering field, Instrumentation and Measurement (I&M) is currently experiencing the impact of the recent rise of Applied AI and in particular Machine Learning (ML) [1]. But I&M and ML use terminology that sometimes sound or look similar, though they might only have a marginal relationship or even be false friends. Therefore,...

The objective of this study is to classify the states of individuals with bipolar disorder. We employ a dataset that uses the Young Mania Recall Scale to distinguish the manic states of patients as: Mania, Hypo-Mania, and Remission. The dataset comprises audio-visual recordings of bipolar disorder patients undergoing a structured interview. Having...

We propose an automatic ternary classification model for Bipolar Disorder (BD) states. As input information, the model uses speech signals from patients' audio-visual recordings of structured interviews. The model classifies the patient's clinical state as Mania, Hypo-Mania, or Remission. We capture Mel-Frequency Cepstral Coefficients (MFCCs) and G...

Bipolar Disorder (BD) is one of the most prevalent mental illnesses in the world. It has a negative impact on people’s social and personal functions. The principal indicator of BD is the extreme swing in the mood ranging from manic to depressive states. This paper addresses the challenge of detecting the BD states by monitoring affective informatio...

We present a hybrid remote rendering method for applications on mobile devices. In our remote rendering approach, we adopt a client-server model, where the server is responsible for rendering high-fidelity models, encoding the rendering results and sending them to the client, while the client renders low-fidelity models and overlays the high-fideli...

Educational systems can benefit from Virtual Reality’s (VR) ability to support experiential learning. In particular, VR based games, especially role-playing serious games (RPGs), can promote learning through the simulation of various educational scenarios. This study proposes an immersive VR-RPG to educate players about the behavior of honeybees. T...

Respiratory Rate (RR) monitoring can inform healthcare providers of early indicators of critical illnesses. However, the obtrusive nature of contact-based sensors for RR monitoring makes them uncomfortable for extended use and vulnerable to movement-derived noise. Hence, camera-based approaches have attracted considerable attention as they enable c...

Recent advances in computer vision and signal processing are enabling researchers to realize mechanisms for the remote monitoring of vital signs. The remote measurement of vital signs, including heart rate (HR), Heart Rate Variability (HRV), and respiratory rate, presents important advantages for patients. For instance, continuous remote monitoring...

We propose a method for the coarse classification of head pose from low-resolution images. We devise a mechanism that uses a cascade of three binary Support Vector Machines (SVM) classifiers. We use two sets of appearance features, Similarity Distance Map (SDM) and Gabor Wavelet (GW) as input to the SVM classifiers. For training, we employ a large...

Recurrent Neural Networks (RNN) process sequential data to capture the time-dependency in the input signal. Training a deep RNN conventionally involves segmenting the data sequence to fit the model into memory. Increasing the segment size permits the model to better capture long-term dependencies at the expense of creating larger models that may no...

Appropriately positioning the Nipple-Areola Complex (NAC) during chest masculinization surgery is a principle determinant of the aesthetic success of the procedure. Nonetheless, today, this positioning process relies on the subjective judgement of the surgeon. Therefore, this paper proposes a novel machine learning solution that leverages Artificia...

Due to the recent fast-paced advances in technology and its potential in ameliorating the writing and reading skills of children with autism, there is a need to update the study published by Knight, McKissick, and Saunders (J Autism Dev Disord 43(11):2628–48) to survey the latest research on the topic. Hence, the objective of this paper is to asses...

Recording and monitoring vital signs is an essential part of home-based healthcare. Using contact sensors to record physiological signals can cause discomfort to patients, especially after prolonged use. Hence, remote physiological measurement approaches have attracted considerable attention, as they do not require physical contact with the patient...

This study investigates the inter-modality influence on the brainstem using a mental task (arithmetic exercise). Frequency Following Responses were recorded in quiet and noise, across four stimuli conditions (No Task, Easy, Medium, and Difficult). For the No Task, subjects were instructed to direct their attention to the presented speech vowel whil...

Cloud computing has recently emerged as a promising paradigm for end-users and service providers. The application of the cloud-computing model to different applications offers many attractive advantages, such as scalability, ubiquity, reliability, and cost reduction to users and providers. By applying this model, the major computational parts of un...

Throughout the last decade, there has been a dramatic decline in daily physical activity among individuals which results in numerous severe health issues, including obesity, cardiovascular diseases, and high blood pressure. Pervasive applications that promote health living present a promising approach for the reduction or prevention of these health...

ECG biometrics is a relatively new technique and its performance is still inferior to that of fingerprint biometrics. However, as opposed to ECG, fingerprint users touch objects and inadvertently leave behind their invisible fingerprints marks. Hackers can lift these invisible marks and gain illicit access to the devices of their victims. Moreover,...

Residential gateways play a key role in providing internet access to home consumers. Nowadays, users in the same home with heterogeneous applications share a common gateway. As such, the gateway becomes the bandwidth bottleneck, leading to impairments and negatively affecting users’ Quality of Experience (QoE). In the case of delay sensitive applic...

Cloud gaming or Gaming as a Service, the newest entry in the online gaming world, leverages the well-known concept of cloud computing to provide real time gaming services to players. This gaming paradigm provides affordable, flexible and high performance solutions for end-users with constrained computing resources and enables them to play high-end...

Medical researchers have always been interested in Heart Rate (HR) and Heart Rate Variability (HRV) analysis. However, nowadays investigators from a variety of other fields are also probing the subject. Recent advancements in non-contact HR and HRV measurement techniques will likely further boost interest in emotional estimation through HRV. Such m...

This paper presents the Simple Internet of Things Enabler (SITE), a smart home solution that allows users to specify and centrally control IoT smart objects. Unlike most existing systems, SITE supports End-User Development. Hence, it defines a simple language for the specification of control rules for smart objects. It also provides a user interfac...

Cloud Gaming enables users to play games using a thin-client, regardless of their location or what platform they use (PCs, laptops, tablets, smartphones). Since the major computational parts of game processing are performed in datacenters, effectively assigning the resources (e.g. memory, bandwidth) to gaming sessions plays a key role in providing...

Online gaming, especially the new paradigm of Cloud Gaming, is advancing the state-of-the-art in interactive networked applications while creating significant business opportunities for game providers. However, online gaming is fundamentally challenged by network latency that impairs the interactive gaming experience and negatively affects players'...

Traditional mobile login methods, like numerical or graphical passwords, are vulnerable to passive attacks. It is common for intruders to gain access to personal information of their victims by watching them enter their passwords into their mobile screens from a close proximity. With this in mind, a mobile biometric authentication algorithm based o...

Cloud based video games bring new opportunities to the gaming industry, and enable end-users to play high-end graphic games on any low-end device without high performance hardware requirements. As the major computational parts of game processing, including user’s input processing, rendering and encoding the game scene, and video streaming are perfo...

This paper presents a transducer network framework that supports the amalgamation of multiple transducers into single wireless nodes. This approach is aimed at decreasing energy consumption by reducing the number of wireless transceivers involved in such networks. To make wireless nodes easily reconfigurable, a plug and play mechanism is applied to...

Artifacts in a heart rate variability (HRV) signal can severely distort the extracted time- and frequency-domain parameters, and thus render the information obtained from the signal potentially unusable. In this paper, we propose an algorithm for nonpathological HRV artifact detection called pattern-based windowed impulse rejection (PWIR) filter. T...

This paper presents an R peak detection algorithm for ECG signals based on the second derivative. Such R peak detection techniques offer low average time error and are computationally inexpensive. However, previously proposed methods based on the second derivatives suffer from low sensitivity and positive predictivity. In this study, we introduce a...

Biofeedback is a well-accepted approach in preventative and alternative healthcare. It is known to promote wellbeing and help prevent and treat a wide variety of disorders related to the human physiology and psychology. With the exceptional growth of wearable sensor technologies, the potential for devising biofeedback systems that blend into everyd...

Tactile haptic support on mobile phones is becoming an indispensable feature of numerous devices. This in turn permits developers to create various tactile icons, or tactons to communicate information through the non-visual and non-auditory modality of touch. Tactons are messages conveyed through various patterns of vibrations. In this paper, we pr...

With the rapid increase of social media resources and services, Internet users are overwhelmed by the vast quantity of social media available. Most recommender systems personalize multimedia content to the users by analyzing two main dimensions of input: content (item), and user (consumer). In this study, we address the issue of how to improve the...

Recommender systems are powerful tools that support the user in their quest to find the multimedia they are looking for. Such systems present multimedia contents or provide recommendations by taking into consideration two dimensions of inputs: content (item), and user (consumer). Little attention has been paid to increasing the quality of the exper...

Some diabetic patients experience difficulties in modulating the grip force magnitude when they manipulate objects using their hands. This difficulty is caused by the sensory loss at the fingertips that impairs the feedback loop between the brain and the aforementioned sensors. In this paper, we present a sensory substitution system called “F-Glove...

Nowadays the World Wide Web increasingly provides rich multimedia contents to its users. With the support of HTML5 techniques and haptic plug-ins for browsers, haptic enabled content can be realized over the Web. However, it is not easy for Web designers that are not proficient in programming or scripting languages (such as javascript), and who do...

In this paper we present SmartInsole, a physical activity and gait measuring system integrated inside an insole. To achieve its goal, it uses force and acceleration sensors that track the wearer’s movements. The device is fitted with a radio transceiver in order to convey measured information to listening computers. Contrary to previous works which...

The current state-of-the-art sensory devices have enabled a reliable tracking of the human's movements. This had a positive impact on the medical field in general and on the physical rehabilitation domain in particular since it created new possibilities to the patients to train from their homes. Home-based rehabilitation systems have emerged as pro...

Heart Rate Variability (HRV) has been garnering a lot of attention from medical researchers and biomedical engineers due to its ability to expose crucial information about the status of the nervous system and the health of the human heart. Although time domain analysis of a HRV signals can yield a wealth of information, frequency domain analysis ha...

Several researchers have highlighted the importance of studying stress and exploring methods to effectively reduce its harmful effects on human wellbeing. Biofeedback is an emerging technology being used as a legitimate preventive health care technique for achieving higher levels of well-being and can also be used for stress management. In this pap...

One common concern with video games today is the lack of physical activity they demand from the user. The design of games and tangible user interfaces (TUIs) that stimulate players and engage them into fun exercising activities is starting to attract the attention of many researchers and companies. This paper presents the software and hardware desi...

Sleep is state of rest necessary for human wellbeing and survival. Low quality sleep during the night affects human performance during the day and can lead to serious illnesses and disorders. In this paper we propose a multimodal system that monitors the quality of sleep and adapts the ambient environment where user sleeps in order to optimize the...

The World Wide Web has gone a long way from its humble beginnings when simple browsers exclusively supported plain textual layouts. Nowadays, it is not uncommon for web browsers to support 3D graphics as part of a colorful palette of contents available for developers in order to relay intended information. With the formal support of WebGL in HTML 5...

Ankle deficiencies occur quite often among poststroke patients and people working in physically demanding professions in general. Computerized telerehabilitation systems have emerged as promising assistive tools for effective diagnosis and rehabilitation interventions. Consequently, the process of recording and analyzing the medical data captured b...

Recently, games that incorporate exertion interfaces have emerged and are gaining attention from both academic researchers and commercial companies. Exergaming refers to video games that promote physical activity through playing. Exergames are believed to be a good method of promoting physical activity in children. Such games encourage children to...

2 wgueaieb@site.uottawa.ca Abstract— In this paper, the design and implementation of a wrist rehabilitation system that is cheap and simple is presented. E-dumbbell consists of a regular dumbbell mounted with an accelerometer and a pair of vibro-tactile actuators that allow the dumbbell interface to interact with a two dimensional Ping-Pong game. T...

Child obesity is one of the major challenges facing modern societies, especially in developed countries. Exergaming tools are considered as effective means to reduce obesity among kids because they require the children to exert physical strength while playing the games. However, most of the existing exergaming tools focus more on the physical well-...

Arm paresis is a very common disability among post-stroke survivors. It is characterized by the inability of a person to perform some specific movements in the arm. A Long term Rehabilitation process plays a key role in the recovery of this kind of disabilities, but such treatment might not be easily accessible to people living away from the cities...

Foot-drop is a common symptom among post stroke patients. It is characterized by the inability of a person to raise his/her foot at the ankle and to drag the toes during swing. To overcome such disability, long-term rehabilitation is crucial. However, such treatment might not be accessible to many people, especially those living far from the cities...

In our previous work we introduced a novel application layer protocol, named ALPHAN, for haptic data communication. In this paper, we present a thorough evaluation of the protocol using a multi-user collaborative haptic application. The benchmark application consists of a simple game where three users attempt to lift a 3D triangular shape and place...

In our previous work we introduced a novel application layer protocol, named ALPHAN, for haptic data communication. The protocol is characterized by three distinguished features: first, it is designed at the application layer to enable the application to define and control the networking parameters. Second, it is made highly customizable using XML-...

The transmission of haptic information over the network has recently received significant attention. The wide spectrum of haptic applications makes it difficult to capture the widely varying requirements of these applications into one generic protocol. In this paper, we introduce ALPHAN (application layer protocol for haptic networking), a novel ap...