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PD Disease State Assessment in Naturalistic Environments Using Deep Learning.

, , , , , and . AAAI, page 1742-1748. AAAI Press, (2015)

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V-TIME: a treadmill training program augmented by virtual reality to decrease fall risk in older adults: study design of a randomized controlled trial, , , , , , , , and . BMC Neurology, (2013)The role of exergaming in Parkinson’s disease rehabilitation: a systematic review of the evidence, , and . Journal of neuroengineering and rehabilitation, 11 (1): 33 (2014)PD Disease State Assessment in Naturalistic Environments Using Deep Learning., , , , , and . AAAI, page 1742-1748. AAAI Press, (2015)Within trial validation and reliability of a single tri-axial accelerometer for gait assessment., , , , and . EMBC, page 5892-5895. IEEE, (2014)Enhancing remote monitoring and classification of motor state in Parkinson's disease using Wearable Technology and Machine Learning., , , , , , , , , and 1 other author(s). MeMeA, page 1-6. IEEE, (2023)Addition of a non-immersive virtual reality component to treadmill training to reduce fall risk in older adults (V-TIME): a randomised controlled trial, , , , , , , , , and 1 other author(s). The Lancet, 388 (10050): 1170--1182 (2016)Designing for and with People with Parkinson's: A Focus on Exergaming., , , , , , , , , and . CHI, page 501-510. ACM, (2015)Towards holistic free-living assessment in Parkinson's disease: Unification of gait and fall algorithms with a single accelerometer., , , , , , and . EMBC, page 651-654. IEEE, (2016)A comparison of methods to detect postural transitions using a single tri-axial accelerometer., , , and . EMBC, page 6234-6237. IEEE, (2014)A Novel Energy-Based Composite Index for Assessing Motor State in Parkinson's Disease by Means of IMU-Based Digital Health Technology., , , , , , , , , and 2 other author(s). I2MTC, page 1-6. IEEE, (2024)