| Digital assessment of falls risk, frailty, and mobility impairment using wearable sensors BR Greene, K McManus, SJ Redmond, B Caulfield, CC Quinn NPJ digital medicine 2 (1), 125, 2019 | 33 | 2019 |
| Development of data-driven metrics for balance impairment and fall risk assessment in older adults K McManus, BR Greene, LGM Ader, B Caulfield IEEE Transactions on Biomedical Engineering 69 (7), 2324-2332, 2022 | 18 | 2022 |
| Unsupervised assessment of balance and falls risk using a smartphone and machine learning BR Greene, K McManus, LGM Ader, B Caulfield Sensors 21 (14), 4770, 2021 | 15 | 2021 |
| Short bouts of gait data and body-worn inertial sensors can provide reliable measures of spatiotemporal gait parameters from bilateral gait data for persons with multiple sclerosis LG Motti Ader, BR Greene, K McManus, N Tubridy, B Caulfield Biosensors 10 (9), 128, 2020 | 15 | 2020 |
| Reliability of inertial sensor based spatiotemporal gait parameters for short walking bouts in community dwelling older adults LGM Ader, BR Greene, K McManus, B Caulfield Gait & Posture 85, 1-6, 2021 | 14 | 2021 |
| Predicting fall counts using wearable sensors: a novel digital biomarker for Parkinson’s disease BR Greene, I Premoli, K McManus, D McGrath, B Caulfield Sensors 22 (1), 54, 2021 | 12 | 2021 |
| Impact of exercise intervention in Parkinson’s disease can be quantified using inertial sensor data and clinical tests K McManus, D McGrath, BR Greene, O Lennon, L McMahon, B Caulfield 2019 41st Annual International Conference of the IEEE Engineering in …, 2019 | 9 | 2019 |
| Are you in pain? Predicting pain and stiffness from wearable sensor activity data N Sett, B Mac Namee, F Calvo, B Caulfield, J Costello, SC Donnelly, ... Artificial Intelligence XXXVI: 39th SGAI International Conference on …, 2019 | 7 | 2019 |
| How many steps to represent individual gait? LGM Ader, K McManus, BR Greene, B Caulfield Companion Proceedings of the 12th ACM SIGCHI Symposium on Engineering …, 2020 | 4 | 2020 |
| Estimating balance, cognitive function, and falls risk using wearable sensors and the sit-to-stand test BR Greene, EP Doheny, K McManus, B Caulfield Wearable technologies 3, e9, 2022 | 1 | 2022 |
| Fall risk stratification of community-living older people. Commentary on the world guidelines for fall prevention and management Topic Group on “Falls among the elderly” of the ITU/WHO Focus Group ... Age and ageing 52 (10), afad162, 2023 | | 2023 |
| Development and Validation of a Smartphone-based Balance and Falls Risk Assessment Protocol K McManus University College Dublin, 2022 | | 2022 |
| Human Movement Analysis: Introduction to Motion Capture and Applications for Health LGM Ader, A Keogh, K McManus, BR Greene, B Caulfield 2020 IEEE International Conference on Healthcare Informatics (ICHI), 1-3, 2020 | | 2020 |
| Short bouts of gait data and inertial sensors can provide reliable measures of spatiotemporal gait parameters from bilateral gait data of participants with multiple sclerosis LGM Ader, BR Greene, K McManus, N Tubridy, B Caulfield | | 2020 |
| Sensor-based Assessment of Falls Risk of the Timed Up and Go in Real-World Settings CC Quinn, BR Greene, K McManus, S Redmond, B Caulfield Oxford University Press, 2019 | | 2019 |
| Recurrent Convolutional Neural Networks as an Approach to Position-Aware Myoelectric Prosthesis Control................ HE Williams, AW Shehata, MR Dawson, E. Scheme, JS Hebert … KJ Bennett, C Pizzolato, S Martelli, JS Bahl, A Sivakumar, GJ Atkins, ... | | |
| Population based screening for assessment of falls and mobilityusing wearable sensors BR Greene, K McManus, B Caulfield | | |
| Automatic fusion of clinical risk factors and inertial sensor data for accurate fall risk assessment during balance assessment BR Greene, K McManus, B Caulfield | | |
