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Rana Zia Ur Rehman
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2020 – today
- 2023
- [j7]Khalid Abdul Jabbar
, Javad Sarvestan
, Rana Zia Ur Rehman, Sue Lord, Ngaire Kerse
, Ruth Teh
, Silvia Del Din
:
Validation of an Algorithm for Measurement of Sedentary Behaviour in Community-Dwelling Older Adults. Sensors 23(10): 4605 (2023) - [j6]Gemma L. Bate, Cameron Kirk, Rana Zia Ur Rehman
, Yu Guan, Alison J. Yarnall, Silvia Del Din
, Rachael A. Lawson
:
The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review. Sensors 23(10): 4881 (2023) - [j5]Mhairi K. Maclean, Rana Zia Ur Rehman
, Ngaire Kerse
, Lynne Taylor
, Lynn Rochester, Silvia Del Din
:
Walking Bout Detection for People Living in Long Residential Care: A Computationally Efficient Algorithm for a 3-Axis Accelerometer on the Lower Back. Sensors 23(21): 8973 (2023) - [c4]Chloe Hinchliffe, Rana Zia Ur Rehman, Diogo Branco, Dan Jackson, Teemu Ahmaniemi, Tiago João Vieira Guerreiro, Meenakshi Chatterjee, Nikolay V. Manyakov
, Ioannis Pandis, Kristen Davies, Victoria Macrae, Svenja Aufenberg, Emma Paulides, Hanna Hildesheim, Jennifer Kudelka, Kirsten Emmert, Geert Van Gassen, Lynn Rochester, C. Janneke van der Woude, Ralf Reilmann, Walter Maetzler, Wan-Fai Ng, Silvia Del Din
:
Identification of Fatigue and Sleepiness in Immune and Neurodegenerative Disorders from Measures of Real-World Gait Variability. EMBC 2023: 1-4 - 2022
- [c3]Emmi Antikainen
, Rana Zia Ur Rehman, Teemu Ahmaniemi, Meenakshi Chatterjee:
Predicting Daytime Sleepiness from Electrocardiography Based Respiratory Rate Using Deep Learning. CinC 2022: 1-4 - 2021
- [c2]Rana Zia Ur Rehman, Lynn Rochester, Alison J. Yarnall
, Silvia Del Din
:
Predicting the Progression of Parkinson's Disease MDS-UPDRS-III Motor Severity Score from Gait Data using Deep Learning. EMBC 2021: 249-252 - 2020
- [j4]Yuhan Zhou
, Rana Zia Ur Rehman
, Clint Hansen
, Walter Maetzler
, Silvia Del Din
, Lynn Rochester
, Tibor Hortobágyi, Claudine J. C. Lamoth
:
Classification of Neurological Patients to Identify Fallers Based on Spatial-Temporal Gait Characteristics Measured by a Wearable Device. Sensors 20(15): 4098 (2020) - [j3]Rana Zia Ur Rehman
, Philipp Klocke
, Sofia Hryniv
, Brook Galna, Lynn Rochester
, Silvia Del Din
, Lisa Alcock
:
Turning Detection During Gait: Algorithm Validation and Influence of Sensor Location and Turning Characteristics in the Classification of Parkinson's Disease. Sensors 20(18): 5377 (2020) - [j2]Rana Zia Ur Rehman
, Yuhan Zhou
, Silvia Del Din
, Lisa Alcock
, Clint Hansen
, Yu Guan, Tibor Hortobágyi, Walter Maetzler
, Lynn Rochester
, Claudine J. C. Lamoth
:
Gait Analysis with Wearables Can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders. Sensors 20(23): 6992 (2020)
2010 – 2019
- 2019
- [j1]Rana Zia Ur Rehman
, Silvia Del Din
, Jian Qing Shi, Brook Galna, Sue Lord, Alison J. Yarnall
, Yu Guan
, Lynn Rochester
:
Comparison of Walking Protocols and Gait Assessment Systems for Machine Learning-Based Classification of Parkinson's Disease. Sensors 19(24): 5363 (2019) - [c1]Matteo Gadaleta
, Giulia Cisotto
, Michele Rossi
, Rana Zia Ur Rehman
, Lynn Rochester
, Silvia Del Din:
Deep Learning Techniques for Improving Digital Gait Segmentation. EMBC 2019: 1834-1837 - [i1]Matteo Gadaleta, Giulia Cisotto, Michele Rossi, Rana Zia Ur Rehman, Lynn Rochester, Silvia Del Din:
Deep Learning Techniques for Improving Digital Gait Segmentation. CoRR abs/1907.04281 (2019)
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