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Author = Moran, Kieran;
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Displaying Results 1 - 25 of 111 on page 1 of 5
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A comparison of asymmetry in athletic groin pain patients and elite rugby union players using analysis of characterising phases
(2014)
Gore, Shane; Richter, Chris; Marshall, Brendan; Franklyn-Miller, Andrew; Moran, Kieran;...
A comparison of asymmetry in athletic groin pain patients and elite rugby union players using analysis of characterising phases
(2014)
Gore, Shane; Richter, Chris; Marshall, Brendan; Franklyn-Miller, Andrew; Moran, Kieran; Blanchfield, Mark; Moore, Barry; Falvey, Eanna
Abstract:
This study compared levels of inter limb asymmetry between field sports players with athletic groin pain and international rugby union players. Three dimensional kinematics and kinetics were recorded for the single leg hurdle hop and side cut movement. Analysis of characterising phases was utilised to identify significant differences in asymmetry between the two groups. The rugby union group had significantly greater asymmetry in some kinematic variables and hip kinetic variables at the beginning of the exercises. Overall however, the athletic groin pain group displayed greater asymmetry, particularly in hip moments compared with the rugby union group. These results suggest that an aspect of rehabilitation for athletic groin pain should focus on reducing asymmetric hip moments.
http://doras.dcu.ie/21196/
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A Demonstration of the PATHway System for Technology-enabled Exercise-based Cardiac Rehabilitation
(2016)
Moran, Kieran; Wei, Haolin; Monaghan, David; Woods, Catherine; O'Connor, Noel E.; ...
A Demonstration of the PATHway System for Technology-enabled Exercise-based Cardiac Rehabilitation
(2016)
Moran, Kieran; Wei, Haolin; Monaghan, David; Woods, Catherine; O'Connor, Noel E.; Zarpalas, Dimitrios; Chatzitofis, Anargyros; Daras, Petros; Piesk, Jens; Pomazanskyi, Andrew
Abstract:
We described an invited demonstration to MMHealth’16 of a platform for technology-enabled exercise-based Cardiac Rehabilitation (CR). The demo focuses on one technical aspect of a much broader lifestyle intervention program i.e. realtime estimation of a user’s adherence to an exercise programm
http://doras.dcu.ie/21346/
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A framework for comprehensive analysis of a swing in sports using low-cost inertial sensors
(2014)
Ahmadi, Amin; Destelle, Francois; Monaghan, David; O'Connor, Noel E.; Richter, Chr...
A framework for comprehensive analysis of a swing in sports using low-cost inertial sensors
(2014)
Ahmadi, Amin; Destelle, Francois; Monaghan, David; O'Connor, Noel E.; Richter, Chris; Moran, Kieran
Abstract:
We present a novel framework to monitor the three- dimensional trajectory (orientation and position) of a golf swing using miniaturized inertial sensors. Firstly we employed a highly accurate and computationally efficient revised gradient descent algorithm to obtain the orientation of a golf club. Secondly, we designed a series of digital filters to determine the backward and forward segments of the swing, enabling us to calculate drift-free linear velocity along with the relative 3D position of the golf club during the entire swing. Finally, the calculated motion trajectory was verified against a ground truth VICON system using Iterative Closest Point (ICP) in conjunction with Principal Component Analysis (PCA). The computationally efficient framework present here achieves a high level of accuracy (r = 0.9885, p < 0.0001) for such a low-cost system. This framework can be utilized for reliable movement technique evaluation and can provide near real-time feedback for athletes in v...
http://doras.dcu.ie/20594/
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A General-Purpose Taxonomy of Computer-Augmented Sports Systems
(2009)
Cahill, Vinny; Haahr, Mads; Reilly, Sean; Barron, Peter; Moran, Kieran
A General-Purpose Taxonomy of Computer-Augmented Sports Systems
(2009)
Cahill, Vinny; Haahr, Mads; Reilly, Sean; Barron, Peter; Moran, Kieran
Abstract:
10.4018/978-1-60566-406-4.ch00
The area of computer-augmented sports is large and complex and spans several disciplines. This chapter presents a general-purpose taxonomy of computer-augmented sports systems, which is intended to assist researchers and designers working in this domain. Allowing systems to be classified with regard to form as well as function, the taxonomy is intended to have several uses, including serving as a clear map to aid in the understanding of the domain and as a tool to help researchers analyse the state-of-the-art by characteristics of systems. The taxonomy also offers a common vocabulary to the multidisciplinary teams that work in computer-augmented sports and can be used to identify sparsely populated regions of the domain as promising areas for future research. The authors present and demonstrate the use of the taxonomy using four example systems selected from an extensive review.
http://hdl.handle.net/2262/89974
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A multi-modal 3D capturing platform for learning and preservation of traditional sports and games
(2015)
Destelle, Francois; Ahmadi, Amin; Moran, Kieran; O'Connor, Noel E.; Zioulis, Nikol...
A multi-modal 3D capturing platform for learning and preservation of traditional sports and games
(2015)
Destelle, Francois; Ahmadi, Amin; Moran, Kieran; O'Connor, Noel E.; Zioulis, Nikolaos; Chatzitofis, Anargyros; Petros, Daras; Zarpalas, Dimitrios; Unzueta, Luis; Rodriguez, Mikel; Goenetxea, Jon; Linaza, Maria Teresa; Magnenat Thalmann, Nadia; Tisserand, Yvain
Abstract:
We present a demonstration of a multi-modal 3D captur- ing platform coupled to a motion comparison system. This work is focused on the preservation of Traditional Sports and Games, namely the Gaelic sports from Ireland and Basque sports from France and Spain. Users can learn, compare and compete in the performance of sporting gestures and compare themselves to real athletes. Our online gesture database provides a way to preserve and display a wide range of sporting gestures. The capturing devices utilised are Kinect 2 sensors and wearable inertial sensors, where the number required varies based on the requested scenario. The fusion of these two capture modalities, coupled to our inverse kinematic algorithm, allow us to synthesize a fluid and reliable 3D model of the user gestures over time. Our novel comparison algorithms provide the user with a per- formance score and a set of comparison curves (i.e. joint angles and angular velocities), providing a precise and valu- able feedback ...
http://doras.dcu.ie/21154/
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A multimodal gamified platform for real-time user feedback in sports performance
(2016)
Monaghan, David; Honohan, Freddie; Ahmadi, Amin; McDaniel, Troy; Tadayon, Ramin; Karpur...
A multimodal gamified platform for real-time user feedback in sports performance
(2016)
Monaghan, David; Honohan, Freddie; Ahmadi, Amin; McDaniel, Troy; Tadayon, Ramin; Karpur, Ajay; Moran, Kieran; O'Connor, Noel E.; Panchanathan, Sethuraman
Abstract:
In this paper we introduce a novel platform that utilises multi-modal low-cost motion capture technology for the de- livery of real-time visual feedback for sports performance. This platform supports the expansion to multi-modal inter- faces that utilise haptic and audio feedback, which scales effectively with motor task complexity. We demonstrate an implementation of our platform within the field of sports performance. The platform includes low-cost motion cap- ture through a fusion technique, combining a Microsoft Kinect V2 with two wrist inertial sensors, which make use of the ac- celerometer and gyroscope sensors, alongside a game-based Graphical User Interface (GUI) for instruction, visual feed- back and gamified score tracking.
http://doras.dcu.ie/21529/
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A prospective investigation of the association between isometric muscle strength and running related Injury among novice and recreational runners
(2019)
Dillon, Sarah; White, Enda; Burke, Aoife; O'Connor, Siobhán; Gore, Shane; Moran, K...
A prospective investigation of the association between isometric muscle strength and running related Injury among novice and recreational runners
(2019)
Dillon, Sarah; White, Enda; Burke, Aoife; O'Connor, Siobhán; Gore, Shane; Moran, Kieran
Abstract:
Introduction Recreational running has many health, social and psychological benefits. However, there is a considerable risk of developing a running related injury (RRI) (1). Therefore, understanding the aetiology of these injuries, with a view to reducing the risk of their development is of paramount importance. Deficits in muscle strength is a proposed risk factor in developing RRIs, though conflicting evidence exists to support this claim (2,3). The majority of this research has been retrospective, limiting the ability to establish a causal relationship. Furthermore, many studies have had small sample sizes, low relative numbers of injured participants or employed isokinetic machines, which have practical limitations. This study aims to prospectively investigate the impact of isometric muscle strength on the likelihood of sustaining a RRI. Methods: One hundred and seventy six injury-free recreational and novice runners (66 females, 110 males, 42.5±9.2 yrs) were recruited. During a...
http://doras.dcu.ie/23556/
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A qualitative exploration of cardiovascular disease patients’ views and experiences with an eHealth cardiac rehabilitation intervention: The PATHway project
(2020)
O'Shea, Orlagh; Woods, Catherine B.; McDermott, Lauri; Buys, Roselien; Cornelis, N...
A qualitative exploration of cardiovascular disease patients’ views and experiences with an eHealth cardiac rehabilitation intervention: The PATHway project
(2020)
O'Shea, Orlagh; Woods, Catherine B.; McDermott, Lauri; Buys, Roselien; Cornelis, Nils; Claes, Jomme; Cornelissen, Veronique; Gallagher, Anne; Newton, Helen; Moyna, Niall M.; McCaffrey, Noel; Susta, Davide; McDermott, Clare; McCormack, Ciara; Budts, Werner; Moran, Kieran
Abstract:
The aim of this study is to explore participants’ views and experiences of an eHealth phase 3 cardiac rehabilitation (CR) intervention: Physical Activity Towards Health (PATHway). Sixty participants took part in the PATHway intervention. Debriefs were conducted after the six-month intervention. All interviews were audio recorded and transcribed verbatim. Transcripts were analysed with Braun and Clarke’s thematic analysis. Forty-four (71%) debriefs were conducted (n = 34 male, mean (SD) age 61 (10) years). Five key themes were identified: (1) Feedback on the components of the PATHway system, (2) Motivation, (3) Barriers to using PATHway, (4) Enablers to using PATHway, and (5) Post programme reflection. There were a number of subthemes within each theme, for example motivation explores participants motivation to take part in PATHway and participants motivation to sustain engagement with PATHway throughout the intervention period. Participant engagement with the components of the PATHw...
http://hdl.handle.net/10344/9002
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A technology platform for enabling behavioural change as a “PATHway” towards better self-management of CVD
(2016)
Moran, Kieran; Wei, Haolin; Monaghan, David; Woods, Catherine; O'Connor, Noel E.; ...
A technology platform for enabling behavioural change as a “PATHway” towards better self-management of CVD
(2016)
Moran, Kieran; Wei, Haolin; Monaghan, David; Woods, Catherine; O'Connor, Noel E.; Zarpalas, Dimitrios; Chatzitofis, Anargyros; Daras, Petros; Piesk, Jens; Pomazanskyi, Andrew
Abstract:
We describe a technology platform developed as part of a novel approach to technology-enabled exercise-based Cardiac Rehabilitation (CR), termed PATHway. We explain the overall concept and explain how technology can facilitate remote participation and better adherence to communitybased long-term Phase III CR. The demo will showcase the user experience of interacting with the PATHway system, including navigation and manual data entry, whilst also demonstrating real-time sensing and analysis of exercise movements and automatic adaptation of exercise based on physiological response.
http://doras.dcu.ie/21345/
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A virtual coaching environment for improving golf swing technique
(2010)
Kelly, Philip; Healy, Aoife; Moran, Kieran; O'Connor, Noel E.
A virtual coaching environment for improving golf swing technique
(2010)
Kelly, Philip; Healy, Aoife; Moran, Kieran; O'Connor, Noel E.
Abstract:
As a proficient golf swing is a key element of success in golf, many golfers make significant effort improving their stroke mechanics. In order to help enhance golfing performance, it is important to identify the performance determining factors within the full golf swing. In addition, explicit instructions on specific features in stroke technique requiring alterations must be imparted to the player in an unambiguous and intuitive manner. However, these two objectives are difficult to achieve due to the subjective nature of traditional coaching techniques and the predominantly implicit knowledge players have of their movements. In this work, we have developed a set of visualisation and analysis tools for use in a virtual golf coaching environment. In this virtual coaching studio, the analysis tools allow for specific areas require improvement in a player's 3D stroke dynamics to be isolated. An interactive 3D virtual coaching environment then allows detailed and unambiguous coach...
http://doras.dcu.ie/15565/
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Activity recognition of local muscular endurance (LME) exercises using an inertial sensor
(2017)
Prabhu, Ghanashyama; Ahmadi, Amin; O'Connor, Noel E.; Moran, Kieran
Activity recognition of local muscular endurance (LME) exercises using an inertial sensor
(2017)
Prabhu, Ghanashyama; Ahmadi, Amin; O'Connor, Noel E.; Moran, Kieran
Abstract:
In this paper, we propose an algorithmic approach for a motion analysis framework to automatically recognize local muscular endurance (LME) exercises and to count their repetitions using a wrist-worn inertial sensor. LME exercises are prescribed for cardiovascular disease rehabilitation. As a technical solution, we propose activity recognition based on machine learning. We developed an algorithm to automatically segment the captured data from all participants. Relevant time and frequency domain features were extracted using a sliding window technique. Principal component analysis (PCA) was applied for dimensionality reduction of the extracted features. We trained 15 binary classifiers using support vector machine (SVM) to recognize individual LME exercises, achieving overall accuracy of more than 98%. We applied grid search technique to obtain the optimal SVM hyperplane parameters. The learning curves (mean ± stdev) for each model is investigated to verify that the models were not o...
http://doras.dcu.ie/22067/
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Aggregating multiple body sensors for analysis in sports
(2008)
Smeaton, Alan F.; Diamond, Dermot; Kelly, Philip; Moran, Kieran; Lau, King-Tong; Morris...
Aggregating multiple body sensors for analysis in sports
(2008)
Smeaton, Alan F.; Diamond, Dermot; Kelly, Philip; Moran, Kieran; Lau, King-Tong; Morris, Deirdre; Moyna, Niall; O'Connor, Noel E.; Zhang, Ke
Abstract:
Real time monitoring of the wellness of sportspersons, during their sporting activity and training, is important in order to maximise performance during the sporting event itself and during training, as well as being important for the health of the sportsperson overall. We have combined a suite of common, off-the-shelf sensors with specialist body sensing technology we are developing ourselves and constructed a software system for recording, analysing and presenting sensed data gathered from a single player during a sporting activity, a football match. We gather readings for heart rate, galvanic skin response, motion, heat flux, respiration, and location (GPS) using on-body sensors, while simultaneously tracking player activity using a combination of a playercam video and pitch-wide video recording. We have aggregated all this sensed data into a single overview of player performance and activity which can be reviewed, post-event. We are currently working on integrating other non-inv...
http://doras.dcu.ie/448/
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An automatic visual analysis system for tennis
(2013)
Connaghan, Damien; Moran, Kieran; O'Connor, Noel E.
An automatic visual analysis system for tennis
(2013)
Connaghan, Damien; Moran, Kieran; O'Connor, Noel E.
Abstract:
This article presents a novel video analysis system for coaching tennis players of all levels, which uses computer vision algorithms to automatically edit and index tennis videos into meaningful annotations. Existing tennis coaching software lacks the ability to automatically index a tennis match into key events, and therefore, a coach who uses existing software is burdened with time-consuming manual video editing. This work aims to explore the effectiveness of a system to automatically detect tennis events. A secondary aim of this work is to explore the bene- fits coaches experience in using an event retrieval system to retrieve the automatically indexed events. It was found that automatic event detection can significantly improve the experience of using video feedback as part of an instructional coaching session. In addition to the automatic detection of key tennis events, player and ball movements are automati- cally tracked throughout an entire match and this wealth of data allo...
http://doras.dcu.ie/17836/
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An evaluation of a 3D multimodal marker-less motion analysis system
(2019)
Rodrigues, Thiago Braga; Ó Catháin, Ciarán; Devine, Declan; Moran, Kieran; O'Conno...
An evaluation of a 3D multimodal marker-less motion analysis system
(2019)
Rodrigues, Thiago Braga; Ó Catháin, Ciarán; Devine, Declan; Moran, Kieran; O'Connor, Noel E.; Murray, Niall
Abstract:
Motion analysis is a technique used by clinicians (among many others) that quantifies human movement by using camera-based systems. Marker-based motion analysis systems have been used across a variety of application domains, from Interactive 3D TeleImmersion (i3DTI) environments to the diagnosis of neuromuscular and musculoskeletal diseases. Although such analysis is performed in several laboratories in many countries, numerous issues exist: (1) the high cost of precise motion capture systems; (2) scarcity of qualified personnel to operate them; (3) expertise required to interpret their results; (4) space requirements to install and store these systems; (5) complexity in terms of measurement protocol required for such systems; (6) limited availability; (7) and in some situations the use of markers means they are unsuitability for certain clinical use cases (e.g. for patients recovering from orthopaedic surgery). In this paper, we present, from a system perspective, an alternative, c...
http://doras.dcu.ie/22993/
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An interactive segmentation tool for quantifying fat in lumbar muscles using axial lumbar-spine MRI
(2015)
Antony, Joseph; McGuinness, Kevin; Welch, Neil; Coyle, Joe; Franklyn-Miller, Andrew; O&...
An interactive segmentation tool for quantifying fat in lumbar muscles using axial lumbar-spine MRI
(2015)
Antony, Joseph; McGuinness, Kevin; Welch, Neil; Coyle, Joe; Franklyn-Miller, Andrew; O'Connor, Noel E.; Moran, Kieran
Abstract:
In this paper we present an interactive tool that can be used to quantify fat infiltration in lumbar muscles, which is useful in studying fat infiltration and lower back pain (LBP) in adults. Currently, a qualitative assessment by visual grading via a 5-point scale is used to study fat infiltration in lumbar muscles from an axial view of lumbar-spine MR Images. However, a quantitative approach (on a continuous scale of 0–100%) may provide a greater insight. In this paper, we propose a method to precisely quantify the fat deposition/infiltration in a user-defined region of the lumbar muscles, which may aid better diagnosis and analysis. The key steps are interactively segmenting the region of interest (ROI) from the lumbar muscles using the well known livewire technique, identifying fatty regions in the segmented region based on variable-selection of threshold and softness levels, automatically detecting the center of the spinal column and fragmenting the lumbar muscles into smaller ...
http://doras.dcu.ie/20946/
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Analysis of characterizing phases on waveforms – an application to vertical jumps
(2014)
Richter, Chris; O'Connor, Noel E.; Moran, Kieran
Analysis of characterizing phases on waveforms – an application to vertical jumps
(2014)
Richter, Chris; O'Connor, Noel E.; Moran, Kieran
Abstract:
The aim of this study is to propose a novel data analysis approach, ‘Analysis of Characterizing Phases’ (ACP), that detects and examines phases of variance within a sample of curves utilizing the time, magnitude and magnitude-time domain; and to compare the findings of ACP to discrete point analysis in identifying performance related factors in vertical jumps. Twenty five vertical jumps were analyzed. Discrete point analysis identified the initial-to-maximum rate of force development (p = .006) and the time from initial-to-maximum force (p = .047) as performance related factors. However, due to inter-subject variability in the shape of the force curves (i.e non-, uni- and bi-modal nature), these variables were judged to be functionally erroneous. In contrast, ACP identified the ability to: apply forces for longer (p < .038), generate higher forces (p < .027) and produce a greater rate of force development (p < .003) as performance related factors. Analysis of Characterizing...
http://doras.dcu.ie/16890/
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Analysis of the 5 iron golf swing when hitting for maximum distance
(2011)
Healy, Aoife; Moran, Kieran; Dickson, Jane; Hurley, Cillian; Smeaton, Alan F.; O'C...
Analysis of the 5 iron golf swing when hitting for maximum distance
(2011)
Healy, Aoife; Moran, Kieran; Dickson, Jane; Hurley, Cillian; Smeaton, Alan F.; O'Connor, Noel E.; Kelly, Philip
Abstract:
Most previous research on golf swing mechanics has focused on the driver club. The aim of this study was to identify the kinematic factors that contribute to greater hitting distance when using the 5 iron club. Three-dimensional marker coordinate data were collected (250 Hz) to calculate joint kinematics at eight key swing events, while a swing analyser measured club swing and ball launch characteristics. Thirty male participants were assigned to one of two groups, based on their ball launch speed (high: 52.9 + 2.1 m +- s71; low: 39.9 + 5.2 m +- s71). Statistical analyses were used to identify variables that differed significantly between the two groups. Results showed significant differences were evident between the two groups for club face impact point and a number of joint angles and angular velocities, with greater shoulder flexion and less left shoulder internal rotation in the backswing, greater extension angular velocity in both shoulders at early downswing, greater left shou...
http://doras.dcu.ie/16580/
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Analysis of the joint kinematics of the 5 iron golf swing
(2009)
Healy, Aoife; Moran, Kieran; Dickson, Jane; Hurley, Cillian; Haahr, Mads; O'Connor...
Analysis of the joint kinematics of the 5 iron golf swing
(2009)
Healy, Aoife; Moran, Kieran; Dickson, Jane; Hurley, Cillian; Haahr, Mads; O'Connor, Noel E.
Abstract:
The purpose of this study was to identify the performance determining factors of the 5-iron golf swing. Joint kinematics were obtained from thirty male golfers using a twelve camera motion analysis system. Participants were divided into two groups, based on their ball launch speed (high vs. low). Those in the high ball speed group were deemed to be the more skillful group. Statistical analysis was used to identify the variables which differed significantly between the two groups, and could therefore be classified as the performance determining factors. The following factors were important to performance success: (i) the ability of the golfer to maintain a large X Factor angle and generate large X Factor angular velocity throughout the downswing, (ii) maintain the left arm as straight as possible throughout the swing, (iii) utilise greater movement of the hips in the direction of the target and a greater extension of the right hip during the downswing and (iv) greater flexion of both...
http://doras.dcu.ie/4616/
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Athletic groin pain: a biomechanical diagnosis
(2015)
Marshall, Brendan; Moran, Kieran; Richter, Chris; Gore, Shane; King, Enda; Franklyn-Mil...
Athletic groin pain: a biomechanical diagnosis
(2015)
Marshall, Brendan; Moran, Kieran; Richter, Chris; Gore, Shane; King, Enda; Franklyn-Miller, Andrew; Strike, Siobhan; Falvey, Eanna
Abstract:
Introduction: Chronic athletic groin pain is commonly experienced in a range of football codes including soccer (Holmich et al. 2014) and gaelic football (Murphy et al. 2012). Much debate surrounds the specific aetiology of AGP but several authors have implicated, at least in part, abnormal movement control and loading in and around the hip and pelvis during play (Rabe et al. 2010, Pizarri et al. 2008). Movement control during change of direction cutting is of particular interest as it is this dynamic movement that is frequently associated with groin pain development (Falvey et al. 2009). No previous studies have attempted to describe the key characteristics of cutting mechanics that may be prevalent in AGP populations, that is, what are the potential biomechanical diagnoses that exist in this cohort. Purpose: To describe the key characteristics of three dimensional cutting mechanics that exist within a large cohort of AGP patients. Methods: Four hundred (n = 400) recre...
http://doras.dcu.ie/20637/
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Automated detection of atrial Fibrillation using R-R intervals and multivariate based classification.
(2016)
Kennedy, Alan; Finlay, Dewar D.; Guldenring, Daniel; Bond, Raymond R.; McLaughlin, Jame...
Automated detection of atrial Fibrillation using R-R intervals and multivariate based classification.
(2016)
Kennedy, Alan; Finlay, Dewar D.; Guldenring, Daniel; Bond, Raymond R.; McLaughlin, James; Moran, Kieran
Abstract:
Automated detection of AF from the electrocardiogram (ECG) still remains a challenge. In this study we investigated two multivariate based classification techniques, Random Forests (RF) and k-nearest neighbor (k − nn), for improved automated detection of AF from the ECG. We have compiled a new database from ECG data taken from existing sources. R-R intervals were then analyzed using four previously described R-R irregularity measurements: (1) The coefficient of sample entropy (CoSEn) (2) The coefficient of variance (CV) (3) Root mean square of the successive differences (RMSSD) and (4) median absolute deviation (MAD). Using outputs from all four R-R irregularity measurements RF and k − nn models were trained. RF classification improved AF detection over CoSEn with overall specificity of 80.1% vs. 98.3% and positive predictive value of 51.8% vs. 92.1% with a reduction in sensitivity, 97.6% vs. 92.8%. k − nn also improved specificity and PPV over CoSEn however the sensitivity of this ...
http://doras.dcu.ie/21933/
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Automated detection of atrial fibrillation using RR intervals and multivariate-based classification
(2016)
Kennedy, Alan; Finlay, Dewar D.; Guldenring, Daniel; Bond, Raymond R.; Moran, Kieran; M...
Automated detection of atrial fibrillation using RR intervals and multivariate-based classification
(2016)
Kennedy, Alan; Finlay, Dewar D.; Guldenring, Daniel; Bond, Raymond R.; Moran, Kieran; McLaughlin, James
Abstract:
Automated detection of AF from the electrocardiogram (ECG) still remains a challenge. In this study, we investigated two multivariate-based classification techniques, Random Forests (RF) and k-nearest neighbor (k-nn), for improved automated detection of AF from the ECG. We have compiled a new database from ECG data taken from existing sources. R-R intervals were then analyzed using four previously described R-R irregularity measurements: (1) the coefficient of sample entropy (CoSEn), (2) the coefficient of variance (CV), (3) root mean square of the successive differences (RMSSD), and (4) median absolute deviation (MAD). Using outputs from all four R-R irregularity measurements, RF and k-nn models were trained. RF classification improved AF detection over CoSEn with overall specificity of 80.1% vs. 98.3% and positive predictive value of 51.8% vs. 92.1% with a reduction in sensitivity, 97.6% vs. 92.8%. k-nn also improved specificity and PPV over CoSEn; however, the sensitivity of this...
http://doras.dcu.ie/21920/
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Automatic activity classification and movement assessment during a sports training session using wearable inertial sensors
(2014)
Ahmadi, Amin; Mitchell, Edmond; Destelle, Francois; Gowing, Marc; Richter, Chris; O...
Automatic activity classification and movement assessment during a sports training session using wearable inertial sensors
(2014)
Ahmadi, Amin; Mitchell, Edmond; Destelle, Francois; Gowing, Marc; Richter, Chris; O'Connor, Noel E.; Moran, Kieran
Abstract:
Motion analysis technologies have been widely used to monitor the potential for injury and enhance athlete performance. However, most of these technologies are expensive, can only be used in laboratory environments and examine only a few trials of each movement action. In this paper, we present a novel ambulatory motion analysis framework using wearable inertial sensors to accurately assess all of an athlete’s activities in an outdoor training environment. We firstly present a system that automatically classifies a large range of training activities using the Discrete Wavelet Transform (DWT) in conjunction with a Random forest classifier. The classifier is capable of successfully classifying various activities with up to 98% accuracy. Secondly, a computationally efficient gradient descent algorithm is used to estimate the relative orientations of the wearable inertial sensors mounted on the thigh and shank of a subject, from which the flexion-extension knee angle is calculated. Finall...
http://doras.dcu.ie/19980/
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Automatic detection of joints and quantification of knee osteoarthritis severity using convolutional neural networks
(2017)
Antony, Joseph; McGuinness, Kevin; Moran, Kieran; O'Connor, Noel E.
Automatic detection of joints and quantification of knee osteoarthritis severity using convolutional neural networks
(2017)
Antony, Joseph; McGuinness, Kevin; Moran, Kieran; O'Connor, Noel E.
Abstract:
This paper introduces a new approach to automatically quantify the severity of knee OA using X-ray images. Automatically quantifying knee OA severity involves two steps: first, automatically localizing the knee joints; next, classifying the localized knee joint images. We introduce a new approach to automatically detect the knee joints using a fully convolutional neural network (FCN). We train convolutional neural networks (CNN) from scratch to automatically quantify the knee OA severity optimizing a weighted ratio of two loss functions: categorical cross-entropy and mean-squared loss. This joint training further improves the overall quantification of knee OA severity, with the added benefit of naturally producing simultaneous multi-class classification and regression outputs. Two public datasets are used to evaluate our approach, the Osteoarthritis Initiative (OAI) and the Multicenter Osteoarthritis Study (MOST), with extremely promising results that outperform existing approaches.
http://doras.dcu.ie/21761/
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Automatic detection, extraction and analysis of unrestrained gait using a wearable sensor system
(2015)
Ahmadi, Amin; Richter, Chris; O'Connor, Noel E.; Moran, Kieran
Automatic detection, extraction and analysis of unrestrained gait using a wearable sensor system
(2015)
Ahmadi, Amin; Richter, Chris; O'Connor, Noel E.; Moran, Kieran
Abstract:
Within this paper we demonstrate thee ffectiveness of a novel body-worn gait monitoring and analysis framework to both accurately and automatically assess gait during ’freeliving’ conditions. Key features of the system include the ability to automatically identify individual steps within specific gait conditions, and the implementation of continuous waveform analysis within an automated system for the generation of temporally normalized data and their statistical comparison across subjects.
http://doras.dcu.ie/20645/
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Automatic estimation of enjoyment levels during cardiac rehabilitation exercise
(2018)
Wei, Haolin; Moran, Kieran; O'Connor, Noel E.
Automatic estimation of enjoyment levels during cardiac rehabilitation exercise
(2018)
Wei, Haolin; Moran, Kieran; O'Connor, Noel E.
Abstract:
Cardiovascular disease (CVD) is the leading cause of premature death and disability in Europe and worldwide. Effective Cardiac Rehabilitation (CR) can significantly improve mortality and morbidity rates, leading to longer independent living and a reduced use of health care resources. However, adherence to such an exercise programme is generally low for a variety of reasons such as lack of time and how enjoyable the CR programme is. In this work, we proposed a method for automatic enjoyment estimation during an exercise which could be used by a clinician to identify when a patient is not enjoying the exercise and therefore at risk of early dropout. In order to evaluate the proposed method, a database was captured where participants perform various of CR exercises. Three set of facial features were extracted and were evaluated using seven different classifiers. The proposed method achieved 49% average accuracy in predicting five different enjoyment level on the newly collected database.
http://doras.dcu.ie/22811/
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