Tazeen Sharif

Bio: Tazeen Sharif is an academic researcher from Ajman University of Science and Technology. The author has contributed to research in topics: Exoskeleton & Lung cancer. The author has an hindex of 1, co-authored 4 publications receiving 9 citations.

Intelligent Exoskeleton for Patients with Paralysis

Abstract: The topic of paralysis has gained a lot of interest among scientist over the last years. Therefore, many projects were made for patients suffering from paralysis, yet none has succeeded in achieving an effective way to give these patients the ability to control their paralyzed body parts. This paper proposes a robotic upper-limb exoskeleton guided using 3D object detection and recognition and controlled via Electroencephalogram (EEG) signals. The proposed system is dedicated to patients with complete monoplegic, hemiplegic and quadriplegic paralysis. The main objective of the system is to give these patients the ability to move their upper-limb, and control a wheelchair using their thoughts, which offers them independence, better life quality and assist them in leading active roles in the society. This system consists of four main components, namely, EEG module, infrared (IR) depth camera, 3D printed upper-limb exoskeleton and a motorized wheelchair. The former two are used as inputs to the system and the collaboration between them shows the uniqueness of the proposed approach. EEG signals are segmented and classified through Fuzzy Logic technique and the results are used for choosing the desired object for grabbing from the surface of a table. Movement to the desired object is executed based on the 3D coordinates obtained from the IR depth camera, while inertial measurement unit (IMU) sensor is placed on the arm as a feedback element to ensure accurate movement and proper safety measures. System prototype showed sufficient results for the proposed idea.

Assistive Technology for Integrating the Visually-Impaired in Mainstream Education and Society

Abstract: The paper presents a comprehensive assistive technology tool, designed and implemented to support the various challenges faced by Visually Impaired (VI) individuals in day-to-day life. The system comprises of smart glasses, processing unit and smart phone application; providing the VI individual with a convenient and cost-effective solution; unlike the conventional methods of Braille-based systems and white stick. The features are developed to facilitate VI with reading in English and Arabic, in-door navigation and face recognition; thus empowering them to lead an independent life. It is also targeted towards enabling the VI to gain professional education and be part of the regular work force. The developed system was tested with the people having visual impairments and was well appreciated.

Diagnostic Approach for Hearing Impairment and Earwax Blockage using Smartphone

Abstract: The rapid increase and furthermore; rising trends in hearing disorders has drawn attention of relevant experts to study, analyze, design and implement solutions for effective management. Often, due to lack of awareness, improper hearing is wrongly concluded as hearing impairment. There are several factors that can adversely affect hearing, one of them being earwax blockage. With timely diagnosis and right approach to cleaning the ear canal, the person's hearing ability can be restored. This paper discusses a smartphone based approach for detecting the ear condition. The system comprises of the bone conduction headset, a regular headset and the developed app. When integrated with the patient, the app results in indicating the type of condition; Hearing Impairment or Earwax Blockage. In case of earwax blockage, the system is capable of indicating the severity of the condition using percentile scale. This cost-effective and portable solution will enable early detection of the condition when incorporated in schools and other health awareness campaigns, thus preventing permanent damage or hearing loss due to earwax blockage.

Deep Learning for Lung Lesion Detection

Abstract: As the most fatal cancer type, early diagnosis of the lung cancer plays an important role for the survival of the patients. Diagnosis of the lung cancer involves screening the patients initially by Computed Tomography (CT) for the presence of lung lesions. This procedure requires expert radiologists which need to go over very large numbers of image slices manually in order to detect and diagnose lung lesions. Unfortunately this is a very time consuming process and its performance is very dependent on the performing radiologist. Thus assisting the radiologists by developing an automated computer aided detection (CAD) system is an interesting research goal. In this regard, as the aim of this paper a pre-trained AlexNet (deep learning) framework is transferred to develop and implement a robust CAD system for the classification of lung images depending on whether they bear a lung lesion or not. High performances of 98.72% sensitivity, 98.35% specificity and 98.48% accuracy are reported as a result.

Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review.

Abstract: Processing and control systems based on artificial intelligence (AI) have progressively improved mobile robotic exoskeletons used in upper-limb motor rehabilitation. This systematic review presents the advances and trends of those technologies. A literature search was performed in Scopus, IEEE Xplore, Web of Science, and PubMed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology with three main inclusion criteria: (a) motor or neuromotor rehabilitation for upper limbs, (b) mobile robotic exoskeletons, and (c) AI. The period under investigation spanned from 2016 to 2020, resulting in 30 articles that met the criteria. The literature showed the use of artificial neural networks (40%), adaptive algorithms (20%), and other mixed AI techniques (40%). Additionally, it was found that in only 16% of the articles, developments focused on neuromotor rehabilitation. The main trend in the research is the development of wearable robotic exoskeletons (53%) and the fusion of data collected from multiple sensors that enrich the training of intelligent algorithms. There is a latent need to develop more reliable systems through clinical validation and improvement of technical characteristics, such as weight/dimensions of devices, in order to have positive impacts on the rehabilitation process and improve the interactions among patients, teams of health professionals, and technology.

Design, Development, and Testing of an Intelligent Wearable Robotic Exoskeleton Prototype for Upper Limb Rehabilitation.

Abstract: Neuromotor rehabilitation and recovery of upper limb functions are essential to improve the life quality of patients who have suffered injuries or have pathological sequels, where it is desirable to enhance the development of activities of daily living (ADLs). Modern approaches such as robotic-assisted rehabilitation provide decisive factors for effective motor recovery, such as objective assessment of the progress of the patient and the potential for the implementation of personalized training plans. This paper focuses on the design, development, and preliminary testing of a wearable robotic exoskeleton prototype with autonomous Artificial Intelligence-based control, processing, and safety algorithms that are fully embedded in the device. The proposed exoskeleton is a 1-DoF system that allows flexion-extension at the elbow joint, where the chosen materials render it compact. Different operation modes are supported by a hierarchical control strategy, allowing operation in autonomous mode, remote control mode, or in a leader-follower mode. Laboratory tests validate the proper operation of the integrated technologies, highlighting a low latency and reasonable accuracy. The experimental result shows that the device can be suitable for use in providing support for diagnostic and rehabilitation processes of neuromotor functions, although optimizations and rigorous clinical validation are required beforehand.

Assistive Technology for Hearing-Impaired and Deaf Students Utilizing Augmented Reality

Abstract: Common universities and colleges worldwide are not equipped with technological techniques that can assist deaf and hearing-impaired students in their education, while few specialized universities are built for deaf students, sign language tutors, or in-class television captioning are included for few majors only. A novel system is proposed and developed to help deaf and hearing-impaired students who are aiming to continue their education outside special centers and communicate normally with the societies that are not sign language educated. By introducing an intelligent software solution developed for affordable augmented reality glasses that will assist students in their educational journey with real-time transcribing, speech emotion recognition, sound indications features, as well as classroom assistive tools.

Assistive technology for visual impairment and trainers at schools for the blind in Delhi.

Abstract: The aim of the study was to assess the availability of assistive technology (AT) for visual impairment and trainers in schools for the blind in Delhi. A cross-sectional study was conducted in 22 of the 24 schools in Delhi. The headteacher of each school was asked about availability of 52 ATs divided into writing, reading, math, sciences, sports, mobility, and daily living, using a questionnaire. Information on availability of trainers was also collected. Of the 52 ATs, the most frequently available were Braille slate with stylus and abacus (>90% of schools), followed by Taylor frame, long cane and talking watch (80% to 90% of schools). Only 11 of 52 AT devices were available in 60% or more of the schools. Tactile-based ATs were more available than vision-based ATs. In the 22 schools, 63 trainers for reading & writing were available (80% of posts), 18 for sciences (59%), 25 for math (70%), and 11 for mobility (50% of posts). Except Braille slate and stylus, there is a huge shortage of AT in these schools. The educational needs and performance of students could be helped by developing and using a list of priority Assistive Products for example, the WHO AP list.

Design of Portable Exoskeleton Forearm for Rehabilitation of Monoparesis Patients Using Tendon Flexion Sensing Mechanism for Health Care Applications

Abstract: Technology plays a vital role in patient rehabilitation, improving the quality of life of an individual. The increase in functional independence of disabled individuals requires adaptive and commercially available solutions. The use of sensor-based technology helps patients and therapeutic practices beyond traditional therapy. Adapting skeletal tracking technology could automate exercise tracking, records, and feedback for patient motivation and clinical treatment interventions and planning. In this paper, an exoskeleton was designed and subsequently developed for patients who are suffering from monoparesis in the upper extremities. The exoskeleton was developed according to the dimensions of a patient using a 3D scanner, and then fabricated with a 3D printer; the mechanism for the movement of the hand is a tendon flexion mechanism with servo motor actuators controlled by an ATMega2560 microcontroller. The exoskeleton was used for force augmentation of the patient’s hand by taking the input from the hand via flex sensors, and assisted the patient in closing, opening, grasping, and picking up objects, and it was also able to perform certain exercises for the rehabilitation of the patient. The exoskeleton is portable, reliable, durable, intuitive, and easy to install and use at any time.