Brian Caulfield

Brian Caulfield
University College Dublin | UCD · School of Public Health, Physiotherapy & Population Science

B.Physio M.Med.Sci. PhD

About

395
Publications
161,038
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
10,285
Citations
Citations since 2016
183 Research Items
7863 Citations
201620172018201920202021202202004006008001,0001,2001,400
201620172018201920202021202202004006008001,0001,2001,400
201620172018201920202021202202004006008001,0001,2001,400
201620172018201920202021202202004006008001,0001,2001,400
Additional affiliations
January 2000 - December 2012
University College Dublin

Publications

Publications (395)
Article
Full-text available
Background Caregivers of People with Dementia (PwD) can experience high levels of distress, which can negatively affect their physical and psychological well-being. We explored factors that influence Health-Related Quality of Life (HRQoL) of caregivers of PwD over 12 months. Methods Fifty-two PwD and their informal caregivers were recruited by con...
Article
Full-text available
Background The prevalence of dementia is increasing worldwide, and innovative strategies are required to meet increasing demands on health services. The Connected HEalth Sustaining home Stay in Dementia (CHESS) Study aimed to provide support to People with Dementia (PwD) and their caregivers in their homes. We aimed to quantitatively assess the acc...
Article
Full-text available
Background To date, little research has been carried out exploring the burden experienced by informal caregivers of People with Dementia (PwD). We explored factors that influence the burden experienced by caregivers of PwD over 12 months. Methods Fifty-two PwD and their informal caregivers were recruited by convenience sampling to the “CHESS” Stud...
Article
Full-text available
Background Research is needed to examine how Quality of Life (QoL) changes as dementia progresses. We explored QoL trajectories over a 12-month period and examined factors that influence QoL in People with Dementia (PwD). Methods Fifty-two PwD and their informal caregivers participated in the “CHESS” Study. Data were collected at five time points...
Article
Full-text available
Background The development of optimal strategies to treat impaired mobility related to ageing and chronic disease requires better ways to detect and measure it. Digital health technology, including body worn sensors, has the potential to directly and accurately capture real-world mobility. Mobilise-D consists of 34 partners from 13 countries who ar...
Article
Full-text available
Background The development of optimal strategies to treat impaired mobility related to ageing and chronic disease requires better ways to detect and measure it. Digital health technology, including body worn sensors, has the potential to directly and accurately capture real-world mobility. Mobilise-D consists of 34 partners from 13 countries who ar...
Preprint
Full-text available
Technological advancements have spurred the usage of machine learning based applications in sports science. Physiotherapists, sports coaches and athletes actively look to incorporate the latest technologies in order to further improve performance and avoid injuries. While wearable sensors are very popular, their use is hindered by constraints on ba...
Article
Full-text available
The loss of mobility is a common trait in multiple health conditions (e.g., Parkinson's disease) and is associated with reduced quality of life. In this context, being able to monitor mobility in the real world, is important. Until recently, the technology was not mature enough for this; but today, miniaturized sensors and novel algorithms promise...
Preprint
Full-text available
Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices (WD) and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validate DMOs estimated using real-world gait data from six different cohorts, focusing on gait...
Article
Full-text available
Background Consumer wearables and smartphone devices commonly offer an estimate of energy expenditure (EE) to assist in the objective monitoring of physical activity to the general population. Alongside consumers, healthcare professionals and researchers are seeking to utilise these devices for the monitoring of training and improving human health....
Chapter
As running has become an increasingly popular method of personal exercise, more and more recreational runners have been testing themselves by participating in endurance events such as marathons. Even though elite endurance runners have been the subject of considerable research, the training habits and performance potential of recreational runners a...
Preprint
Background: Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim of this study is to propose and validate a multi-task and multi-phase protocol for simulating...
Conference Paper
Advances in sensor technology have provided an opportunity to measure gait characteristics using body-worn inertial measurement units (IMUs). Whilst research investigating the validity of IMUs in reporting gait characteristics is extensive, research investigating the reliability of IMUs is limited. This study aimed to investigate the inter-session...
Conference Paper
When using wearable sensors for measurement and analysis of human performance, it is often necessary to integrate and synchronise data from separate sensor systems. This paper describes a synchronization technique between IMUs attached to the shanks and insoles attached at the feet and aims to solve the need to compute the ankle joint angle, which...
Article
Full-text available
Background Technological advances have recently made possible the estimation of maximal oxygen consumption (VO2max) by consumer wearables. However, the validity of such estimations has not been systematically summarized using meta-analytic methods and there are no standards guiding the validation protocols. Objective The aim was to (1) quantitativ...
Article
Full-text available
The five times sit-to-stand test (FTSS) is an established functional test, used clinically as a measure of lower-limb strength, endurance and falls risk. We report a novel method to estimate and classify cognitive function, balance impairment and falls risk using the FTSS and body-worn inertial sensors. 168 community dwelling older adults received...
Preprint
Full-text available
Background The development of optimal strategies to treat impaired mobility related to ageing and chronic disease requires better ways to detect and measure it. Digital health technology, including body worn sensors, has the potential to directly and accurately capture real-world mobility. Mobilise-D consists of 34 partners from 13 countries who ar...
Preprint
Full-text available
Remote monitoring of motor functions is a powerful approach for health assessment, especially among the elderly population or among subjects affected by pathologies that negatively impact their walking capabilities. This is further supported by the continuous development of wearable sensor devices, which are getting progressively smaller, cheaper,...
Article
Ageing incurs a natural decline of postural control which has been linked to an increased risk of falling. Accurate balance assessment is important in identifying postural instability and informing targeted interventions to prevent falls in older adults. Inertial sensor (IMU) technology offers a low-cost means for objective quantification of human...
Chapter
Full-text available
In this paper we present an approach for the classification and interpretation of human motion from video data. Our work builds upon the state-of-the-art advances in the area of Human Pose Estimation for video and Multivariate Time Series Classification and Interpretation. Our goal is to facilitate physiotherapists, coaches and rehabilitation patie...
Chapter
This paper introduces the use of time-series barycenter averaging as a means of providing aggregate representations of repetition-based exercises. Time-series averaging is not straightforward as small misalignments can cause key features to be lost. Our evaluation focuses on the Forward Lunge exercise, an exercise that is used for strengthening, sc...
Chapter
Time Series data collected from wearable sensors such as Inertial Measurement Units (IMU) are becoming popular for use in classification tasks in the exercise domain. The data from these IMU sensors tend to have multiple channels of data as well as the potential to augment new time series based features. However, this data also tends to have high c...
Article
Full-text available
People with Parkinson’s disease (PD) experience significant impairments to gait and balance; as a result, the rate of falls in people with Parkinson’s disease is much greater than that of the general population. Falls can have a catastrophic impact on quality of life, often resulting in serious injury and even death. The number (or rate) of falls i...
Article
Full-text available
Introduction Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations by quantifying digital mobility outcomes (DMOs)...
Article
Full-text available
The Y Balance Test (YBT) is a dynamic balance assessment typically used in sports medicine. This work proposes a deep learning approach to automatically score this YBT by estimating the normalized reach distance (NRD) using a wearable sensor to register inertial signals during the movement. This paper evaluates several signal processing techniques...
Article
Background The number of mobile health (mHealth) apps released for musculoskeletal (MSK) injury treatment and self-management with home exercise programs (HEPs) has risen rapidly in recent years as digital health interventions are explored and researched in more detail. As this number grows, it is becoming increasingly difficult for users to naviga...
Article
Background: Effective self-care is an important factor in the successful management of patients with heart failure (HF). Despite the importance of self-care, most patients with HF are not adequately taught the wide range of skills required to become proficient in self-care. Digital health technology (DHT) may provide a novel solution to support pa...
Preprint
BACKGROUND Effective self-care is an important factor in the successful management of patients with heart failure (HF). Despite the importance of self-care, most patients with HF are not adequately taught the wide range of skills required to become proficient in self-care. Digital health technology (DHT) may provide a novel solution to support pati...
Article
Full-text available
Background The World Health Organisation’s global strategy for digital health emphasises the importance of patient involvement. Understanding the usability and acceptability of wearable devices is a core component of this. However, usability assessments to date have focused predominantly on healthy adults. There is a need to understand the patient...
Chapter
When training for endurance activities, such as the marathon, the risk of injury is ever-present, especially for first-time or inexperienced athletes. And because injuries depend on various factors, there is an opportunity to provide athletes with greater levels of support and guidance when it comes to the risks associated with their training. Henc...
Article
Full-text available
Assessment of health and physical function using smartphones (mHealth) has enormous potential due to the ubiquity of smartphones and their potential to provide low cost, scalable access to care as well as frequent, objective measurements, outside of clinical environments. Validation of the algorithms and outcome measures used by mHealth apps is of...
Article
Full-text available
Background The use of wearable sensor technology to collect patient health data, such as gait and physical activity, offers the potential to transform healthcare research. To maximise the use of wearable devices in practice, it is important that they are usable by, and offer value to, all stakeholders. Although previous research has explored partic...
Article
Full-text available
Machine learning models are being utilized to provide wearable sensor-based exercise biofeedback to patients undertaking physical therapy. However, most systems are validated at a technical level using lab-based cross validation approaches. These results do not necessarily reflect the performance levels that patients and clinicians can expect in th...
Article
Full-text available
Background When performing quantitative analysis of gait in older adults we need to strike a balance between capturing sufficient data for reliable measurement and avoiding issues such as fatigue. The optimal bout duration is that which contains sufficient gait cycles to enable a reliable and representative estimate of gait performance. Research q...
Conference Paper
Full-text available
In this paper we present an approach for the classification and interpretation of human motion from video data. Our work builds upon the state-of-the-art advances in the area of Human Pose Estimation for video and Multivariate Time Series Classification and Interpretation. Our goal is to facilitate physiotherapists, coaches and rehabilitation patie...
Article
Full-text available
Assessing vital signs such as heart rate (HR) by wearable devices in a lifestyle-related environment provides widespread opportunities for public health related research and applications. Commonly, consumer wearable devices assessing HR are based on photoplethysmography (PPG), where HR is determined by absorption and reflection of emitted light by...
Article
Full-text available
Effective self-management of chronic obstructive pulmonary disease (COPD) can lead to increased patient control and reduced health care costs. However, both patients and healthcare professionals encounter significant challenges. Digital health interventions, such as smart oximeters and COPD self-management applications, promise to enhance the manag...
Conference Paper
Full-text available
Digital biofeedback systems (DBS) which use inertial measurement units (IMUs) can support patients during home rehabilitation. Models which accurately segment IMU data for rehabilitation exercises are required to provide biofeedback but assessing accuracy in a clinical context is challenging due to technical and patient-related factors. In this pap...
Article
Full-text available
Background: Data derived from wearable activity trackers may provide important clinical insights into disease progression and response to intervention, but only if clinicians can interpret it in a meaningful manner. Longitudinal activity data can be visually presented in multiple ways, but research has failed to explore how clinicians interact wit...
Article
Full-text available
PurposeConcurrent neuromuscular electrical stimulation (NMES) involving sub-tetanic low frequency and tetanic high frequency which targets aerobic and muscular fitness is a potential alternative to conventional exercise in cancer rehabilitation. However, its safety and feasibility in patients with advanced cancer are unknown. The aim of this feasib...
Chapter
Training for the marathon, especially a first marathon, is always a challenge. Many runners struggle to find the right balance between their workouts and their recovery, often leading to sub-optimal performance on race-day or even injury during training. We describe and evaluate a novel case-based reasoning system to help marathon runners as they t...
Article
Full-text available
Background: Wearable sensors allow researchers to remotely capture digital health data, including physical activity, which may identify digital biomarkers to differentiate healthy and clinical cohorts. To date, research has focused on high-level data (e.g., overall step counts) which may limit our insights to whether people move differently, rathe...
Article
Full-text available
Wearable devices equipped with inertial sensors enable objective gait assessment for persons with multiple sclerosis (MS), with potential use in ambulatory care or home and community-based assessments. However, gait data collected in non-controlled settings are often fragmented and may not provide enough information for reliable measures. This pape...
Article
Full-text available
Background: Single-item athlete self-report measures consist of a single question to assess a dimension of wellbeing. These methods are recommended and frequently used for athlete monitoring, yet their uniformity has not been well assessed, and we have a limited understanding of their relationship with measures of training load. Objective: To inv...
Article
Full-text available
Introduction Digital home rehabilitation systems require accurate segmentation methods to provide appropriate feedback on repetition counting and exercise technique. Current segmentation methods are not suitable for clinical use; they are not highly accurate or require multiple sensors, which creates usability problems. We propose a model for accur...
Article
Full-text available
The primary aim of this study was to investigate the functional, physiological and subjective responses to NMES exercise in cancer patients. Participants with a cancer diagnosis, currently undergoing treatment, and an had an Eastern Cooperative Oncology Group (ECOG) performance status (ECOG) of 1 and 2 were recommended to participate by their oncol...
Article
Full-text available
Background: Physiotherapy-led home rehabilitation after breast cancer surgery can protect against the development of upper limb dysfunction and other disabling post consequences of surgery. A variety of barriers can limit physical rehabilitation outcomes, and patients may benefit from more support during this time. MHealth systems can assist patie...
Article
Full-text available
The purpose of this study was to determine if National Collegiate Athletics Association Division 1 American Football and Ice Hockey athletes with a history of concussion have impaired dynamic balance control when compared to healthy control athletes. This cross‐sectional observational study recruited 146 athletes; 90 control athletes and 56 athlete...
Conference Paper
A growing body of evidence has highlighted that inertial sensor data can increase the sensitivity and clinical utility of the Y Balance Test, a commonly used clinical dynamic balance assessment. While early work has demonstrated the value of a single lumbar worn inertial sensor in quantifying dynamic balance control, no research has investigated if...
Article
Full-text available
Digital data trails from disparate sources covering different aspects of student life are stored daily in most modern university campuses. However, it remains challenging to (i) combine these data to obtain a holistic view of a student, (ii) use these data to accurately predict academic performance, and (iii) use such predictions to promote positiv...
Article
Full-text available
The current sports concussion assessment paradigm lacks reliability, has learning effects and is not sufficiently challenging for athletes. As a result, subtle deficits in sensorimotor function may be unidentified, increasing the risk of future injury. This study examined if the inertial-sensor instrumented Y Balance test could capture concussion i...