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Shahin Basiratzadeh

Bio: Shahin Basiratzadeh is an academic researcher from University of Ottawa. The author has contributed to research in topics: Augmented reality & Fiducial marker. The author has an hindex of 2, co-authored 2 publications receiving 7 citations. Previous affiliations of Shahin Basiratzadeh include Ottawa Hospital Research Institute.

Papers
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Proceedings ArticleDOI
01 Jul 2020
TL;DR: A novel Android smartphone augmented-reality-based application was developed using the AprilTag2 fiducial marker system and obtained valid and reliable angle and distance measurements with smartphone positions and cameras that would be expected in practice.
Abstract: Marker tracking for postural and range of motion (ROM) measurements transcends multiple disciplines (e.g., healthcare, ergonomics, engineering). A viable real-time mobile application is currently lacking for measuring limb angles and body posture. To address this need, a novel Android smartphone augmented-reality-based application was developed using the AprilTag2 fiducial marker system. To evaluate the app, two markers were printed on paper and attached to a wall. A Samsung S6 mobile phone was fixed on a tripod, parallel to the wall. The smartphone app tracked and recorded marker orientation and 2D position data in the camera frame, from front and rear cameras, for different smartphone placements. The average error between mobile phone and measured angles was less than 1 degree for all test settings (back camera=0.29°, front camera=0.33°, yaw rotation=0.75°, tilt rotation=0.22°). The average error between mobile phone and measured distance was less than 4 mm for all test settings (back camera=1.8 mm, front camera=2.5 mm, yaw rotation=3 mm, tilt rotation=3.8 mm). Overall, the app obtained valid and reliable angle and distance measurements with smartphone positions and cameras that would be expected in practice. Thus, this app is viable for clinical ROM and posture assessments.

7 citations

Proceedings ArticleDOI
01 Apr 2019
TL;DR: This research reviewed and evaluated various fiducial marker systems by developing an Android mobile application for real-time biomechanical measurement and selected AprilTag2 as the best fiducIAL marker option for this application.
Abstract: Marker-based measurement has been used to assess human body positioning, but human marker tracking has yet to make the transition from the laboratory to personal computing devices, such as smartphones. A novel smartphone-based approach could use a fiducial marker system. Fiducial markers are applicable to augmented reality, robotics, and other applications where a camera-object pose is required and tracked. However, few fiducial systems can be implemented on a mobile phone because of the processing requirements for identifying and tracking the tags in realtime. In augmented reality, virtual information is shared with the real world to further enhance a person’s view of the environment; therefore, this illusion is directly associated with good registration of both virtual and real worlds. Measurement applications also require accurate and fast registration so that real objects are in alignment with virtual objects in real-time. Our research reviewed and evaluated various fiducial marker systems by developing an Android mobile application for real-time biomechanical measurement. A test was designed for two nominated fiducial systems to compare their speed and robustness on the mobile phone. AprilTag2 was selected as the best fiducial marker option for this application.

7 citations

Journal ArticleDOI
28 May 2022-BioMed
TL;DR: A novel Android smartphone augmented-reality-based application was developed and evaluated to enable real-time AprilTag2 marker measurement at the point of patient contact and obtained valid and reliable angle measurements for postural and ROM assessments using the smartphone’s front camera.
Abstract: Human posture and range of motion (ROM) measurements are important health indicators for identifying abnormalities from various disorders (e.g., scoliosis, musculoskeletal disorders, pain syndromes). A viable real-time mobile application for measuring body posture and ROM is currently lacking. To address this need, a novel Android smartphone augmented-reality-based application was developed and evaluated to enable real-time AprilTag2 marker measurement at the point of patient contact (Biomechanical Augmented Reality-Marker, BAR-M). Mobile app performance was evaluated on a body opponent bag (BOB) and 15 healthy participants by comparing smartphone app and Vicon motion analysis output (pelvis, shoulder, arm, torso angles). A Samsung Galaxy smartphone recorded live video, calculated AprilTag orientations and angle of “a line connecting the center of two tags”, and displayed outcomes in real time. For the BOB test, the absolute difference between Vicon and smartphone angles were 0.09° ± 0.05° for hip, 0.09° ± 0.06° for shoulder, and 0.69° for arm abduction. For the participant test, the absolute mean angle differences were 1.70° ± 0.23° for hip, 1.34° ± 0.27° for shoulder, and 11.18° ± 3.68° for arm abduction. Overall, the app obtained valid and reliable angle measurements for postural and ROM assessments using the smartphone’s front camera. Arm abduction results were affected by clothing movement that caused Vicon markers to move differently from AprilTag markers. Thus, with appropriate measurement methods, this real-time smartphone app is a viable tool to facilitate immediate clinical decision making based on human posture and ROM assessments.

3 citations

Journal ArticleDOI
TL;DR: In this paper , a discrepancy was found between radiologists' reports and surgeons' assessments of scoliosis in adolescents with AIS, using the Cobb angle measurement, which is the standard method for quantification.
Abstract: # Abstract 57. Radiographic reporting in adolescent idiopathic scoliosis: Is there a discrepancy comparing radiologists’ reports and surgeons’ assessments? {#article-title-2} Cobb angle measurement is the standard method for quantification of scoliosis in adolescent idiopathic scoliosis (AIS),

Cited by
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Journal ArticleDOI
TL;DR: The article proposes to divide the various phases of an MAR application into sequential and parallel tasks and attempts to offload the task to the nearby devices with the help of Deep Reinforcement Algorithm (DRL) depending on transmission, task and energy constraints.

11 citations

Proceedings ArticleDOI
01 Jul 2020
TL;DR: A novel Android smartphone augmented-reality-based application was developed using the AprilTag2 fiducial marker system and obtained valid and reliable angle and distance measurements with smartphone positions and cameras that would be expected in practice.
Abstract: Marker tracking for postural and range of motion (ROM) measurements transcends multiple disciplines (e.g., healthcare, ergonomics, engineering). A viable real-time mobile application is currently lacking for measuring limb angles and body posture. To address this need, a novel Android smartphone augmented-reality-based application was developed using the AprilTag2 fiducial marker system. To evaluate the app, two markers were printed on paper and attached to a wall. A Samsung S6 mobile phone was fixed on a tripod, parallel to the wall. The smartphone app tracked and recorded marker orientation and 2D position data in the camera frame, from front and rear cameras, for different smartphone placements. The average error between mobile phone and measured angles was less than 1 degree for all test settings (back camera=0.29°, front camera=0.33°, yaw rotation=0.75°, tilt rotation=0.22°). The average error between mobile phone and measured distance was less than 4 mm for all test settings (back camera=1.8 mm, front camera=2.5 mm, yaw rotation=3 mm, tilt rotation=3.8 mm). Overall, the app obtained valid and reliable angle and distance measurements with smartphone positions and cameras that would be expected in practice. Thus, this app is viable for clinical ROM and posture assessments.

7 citations

Journal ArticleDOI
TL;DR: This paper introduces an accurate marker registration technique that can be used in huge structures and proposes a method that utilizes the natural feature points and the marker corner points in the optimization step simultaneously to improve the precision of marker registration.
Abstract: As the scale of offshore plants has gradually increased, the amount of management points has significantly increased. Therefore, there are needs for innovative process control, quality management, and an installation support system to improve productivity and efficiency for timely construction. In this paper, we introduce a novel approach to deal with these issues using augmented reality (AR) technology. The core of successful AR implementation is up to scene matching through accurate pose (position and alignment) estimation using an AR camera. To achieve this, this paper first introduces an accurate marker registration technique that can be used in huge structures. In order to improve the precision of marker registration, we propose a method that utilizes the natural feature points and the marker corner points in the optimization step simultaneously. Subsequently, a method of precisely generating AR scenes by utilizing these registered markers is described. Finally, to validate the proposed method, the best practices and its effects are introduced. Based on the proposed AR system, construction workers are now able to quickly navigate to onboard destinations by themselves. In addition, they are able to intuitively install and inspect outfitting parts without paper drawings. Through field tests and surveys, we confirm that AR-based inspection has a significant time-saving effect compared to conventional drawing-based inspection.

5 citations

Journal ArticleDOI
28 May 2022-BioMed
TL;DR: A novel Android smartphone augmented-reality-based application was developed and evaluated to enable real-time AprilTag2 marker measurement at the point of patient contact and obtained valid and reliable angle measurements for postural and ROM assessments using the smartphone’s front camera.
Abstract: Human posture and range of motion (ROM) measurements are important health indicators for identifying abnormalities from various disorders (e.g., scoliosis, musculoskeletal disorders, pain syndromes). A viable real-time mobile application for measuring body posture and ROM is currently lacking. To address this need, a novel Android smartphone augmented-reality-based application was developed and evaluated to enable real-time AprilTag2 marker measurement at the point of patient contact (Biomechanical Augmented Reality-Marker, BAR-M). Mobile app performance was evaluated on a body opponent bag (BOB) and 15 healthy participants by comparing smartphone app and Vicon motion analysis output (pelvis, shoulder, arm, torso angles). A Samsung Galaxy smartphone recorded live video, calculated AprilTag orientations and angle of “a line connecting the center of two tags”, and displayed outcomes in real time. For the BOB test, the absolute difference between Vicon and smartphone angles were 0.09° ± 0.05° for hip, 0.09° ± 0.06° for shoulder, and 0.69° for arm abduction. For the participant test, the absolute mean angle differences were 1.70° ± 0.23° for hip, 1.34° ± 0.27° for shoulder, and 11.18° ± 3.68° for arm abduction. Overall, the app obtained valid and reliable angle measurements for postural and ROM assessments using the smartphone’s front camera. Arm abduction results were affected by clothing movement that caused Vicon markers to move differently from AprilTag markers. Thus, with appropriate measurement methods, this real-time smartphone app is a viable tool to facilitate immediate clinical decision making based on human posture and ROM assessments.

3 citations