Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research

Siena, Francesco Luke; Byrom, Bill; Watts, Paul; Breedon, Philip

doi:10.1007/s10916-018-0905-x

Cited by 67 publications

(40 citation statements)

References 19 publications

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“…The motorist remote-controls the procedure, and also fractures can be filled by the system. When compared with a sealing surgery could have a crew daily to perform 2 or two kilometers per hour Robots can also be currently assisting remove debris and litter, just the other labor intensive operation [9].These actions linked to works could be gained.-Development of the platform to get air while operator finishes final fragile regions of the task .-A masonry robot which pre-plans its activities. During this undertaking, including a world-wide placement detector adjusts deviations of their robot software Center Point (TCP) because of inactive deflection of this manipulator structure [10].…”

Section: Automationmentioning

confidence: 99%

Robotics in Construction: Opportunities and Challenges

2019

IJRTE

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Building and construction is one of the major industries around the world. Construction industry is labour-intensive and is conducted in dangerous situations; therefore the importance of construction robotics has grown rapidly. Applications and activities of robotics and automation in this industry started in the early 90s aiming to optimize equipment operations, improve safety, enhance perception of workspace and furthermore, ensure quality environment for building occupants. The main goal of this paper is to convince building designers and managers to incorporate robotic systems when managing modern buildings. This paper studies recent applications for robots and automation in the construction industry and sets opportunities and challenges through a new framework for better planning and control of construction equipment operation.

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Section: Automationmentioning

confidence: 99%

Robotics in Construction: Opportunities and Challenges

2019

IJRTE

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“…Despite the fact that Intel RealSense devices have only appeared on the market in recent years, they have been adopted in several fields. Among the many applications we find posture and gesture interaction systems and human interaction design [18][19][20][21][22], Interactive AI toy for children [23], security and robotics [24][25][26], and also medical and human care [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Metrological and Critical Characterization of the Intel D415 Stereo Depth Camera

Carfagni¹,

Furferi²,

Governi³

et al. 2018

Preprint

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Low-cost RGB-D cameras are increasingly used in several research fields including human-machine interaction, safety, robotics, biomedical engineering and even Reverse Engineering applications. Among the plethora of commercial devices, the Intel RealSense cameras proved to be among the best suitable devices, providing a good compromise between cost, ease of use, compactness and precision. Released on the market in January 2018, the new Intel model RealSense D415 has a wide acquisition range (i.e. ~160-10000 mm) and a narrow field of view to capture objects in rapid motion. Given the unexplored potential of this new device, especially when used as a 3D scanner, the present work aims to characterize and to provide metrological considerations on the RealSense D415. In particular, tests are carried out to assess the device performances in the near range (i.e. 100-1000 mm). Characterization is performed by integrating the guidelines of the existing standard (i.e. the German VDI/VDE 2634 part 2 normative) with a number of literature-based strategies. Performance analysis is finally compared against latest close-range sensors, thus providing a useful guidance for researchers and practitioners aiming to use RGB-D cameras in Reverse Engineering applications.

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“…The increasing availability of accurate, low-cost depth sensors, along with the development of efficient face alignment algorithms provide a great opportunity to introduce novel and intelligent systems in clinical environments [15], [16]. Previous studies demonstrated the feasibility of 3D video-based approaches for the assessment of motor speech disorders in patients with Parkinson's disease and amyotrophic lateral sclerosis (ALS) [17]- [19].…”

Section: Introductionmentioning

confidence: 99%

Automatic Detection of Orofacial Impairment in Stroke

Bandini¹,

Green²,

Richburg³

et al. 2018

Interspeech 2018

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Stroke is a devastating condition that affects the ability of people to communicate through speech, leading to social isolation and poor quality of life. The quantitative evaluation of speech and orofacial movements is essential for assessing the impairment and identifying treatment targets. However, to our knowledge, a tool for the automatic orofacial assessment, which considers multiple aspects of orofacial impairment (e.g., range of motion in addition to asymmetry), has not been developed for this clinical population. In this work, we tested a video-based approach for the automatic orofacial assessment in stroke survivors, combining low-cost depth sensor and face alignment algorithms for extracting facial features. Twelve patients post-stroke and 11 control subjects were evaluated during speech and non-speech tasks. By using a small featureset representing range of motion and asymmetry of face movements, it was possible to discriminate patients poststroke from control subjects with high accuracy (87%). Further insights on the choice of the task and face alignment algorithm are provided, demonstrating that a non-parametric approach such as SDM can provide better results. Through this work we demonstrated the feasibility of an objective tool to support clinicians in the assessment of speech and orofacial impairment post-stroke.

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Utilising the Intel RealSense Camera for Measuring Health Outcomes in Clinical Research

Cited by 67 publications

References 19 publications

Robotics in Construction: Opportunities and Challenges

Robotics in Construction: Opportunities and Challenges

Metrological and Critical Characterization of the Intel D415 Stereo Depth Camera

Automatic Detection of Orofacial Impairment in Stroke

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