| The need to approximate the use-case in clinical machine learning S Saeb, L Lonini, A Jayaraman, DC Mohr, KP Kording Gigascience 6 (5), gix019, 2017 | 262 | 2017 |
| Wearable sensors for Parkinson’s disease: which data are worth collecting for training symptom detection models L Lonini, A Dai, N Shawen, T Simuni, C Poon, L Shimanovich, ... NPJ digital medicine 1 (1), 64, 2018 | 184 | 2018 |
| Using and understanding cross-validation strategies. Perspectives on Saeb et al. MA Little, G Varoquaux, S Saeb, L Lonini, A Jayaraman, DC Mohr, ... GigaScience 6 (5), gix020, 2017 | 159 | 2017 |
| Role of data measurement characteristics in the accurate detection of Parkinson’s disease symptoms using wearable sensors N Shawen, MK O’Brien, S Venkatesan, L Lonini, T Simuni, JL Hamilton, ... Journal of neuroengineering and rehabilitation 17, 1-14, 2020 | 84 | 2020 |
| Video-based pose estimation for gait analysis in stroke survivors during clinical assessments: a proof-of-concept study L Lonini, Y Moon, K Embry, RJ Cotton, K McKenzie, S Jenz, A Jayaraman Digital Biomarkers 6 (1), 9-18, 2022 | 68 | 2022 |
| Humans can integrate augmented reality feedback in their sensorimotor control of a robotic hand F Clemente, S Dosen, L Lonini, M Markovic, D Farina, C Cipriani IEEE Transactions on Human-Machine Systems 47 (4), 583-589, 2016 | 66 | 2016 |
| Voodoo machine learning for clinical predictions S Saeb, L Lonini, A Jayaraman, DC Mohr, KP Kording Biorxiv, 059774, 2016 | 54 | 2016 |
| Rapid screening of physiological changes associated with COVID-19 using soft-wearables and structured activities: a pilot study L Lonini, N Shawen, O Botonis, M Fanton, C Jayaraman, ... IEEE Journal of Translational Engineering in Health and Medicine 9, 1-11, 2021 | 49 | 2021 |
| Robust active binocular vision through intrinsically motivated learning L Lonini, S Forestier, C Teulière, Y Zhao, BE Shi, J Triesch Frontiers in neurorobotics 7, 20, 2013 | 47 | 2013 |
| Fall detection in individuals with lower limb amputations using mobile phones: machine learning enhances robustness for real-world applications N Shawen, L Lonini, CK Mummidisetty, I Shparii, MV Albert, K Kording, ... JMIR mHealth and uHealth 5 (10), e8201, 2017 | 40 | 2017 |
| Self-calibrating smooth pursuit through active efficient coding C Teulière, S Forestier, L Lonini, C Zhang, Y Zhao, B Shi, J Triesch Robotics and Autonomous Systems 71, 3-12, 2015 | 34 | 2015 |
| An internal model for acquisition and retention of motor learning during arm reaching L Lonini, L Dipietro, L Zollo, E Guglielmelli, HI Krebs Neural computation 21 (7), 2009-2027, 2009 | 30 | 2009 |
| Dispensing an enzyme-conjugated solution into an ELISA plate by adapting ink-jet printers L Lonini, D Accoto, S Petroni, E Guglielmelli Journal of biochemical and biophysical methods 70 (6), 1180-1184, 2008 | 30 | 2008 |
| Activity recognition in patients with lower limb impairments: do we need training data from each patient? L Lonini, A Gupta, K Kording, A Jayaraman 2016 38th Annual International Conference of the IEEE Engineering in …, 2016 | 29 | 2016 |
| Autonomous learning of active multi-scale binocular vision L Lonini, Y Zhao, P Chandrashekhariah, BE Shi, J Triesch 2013 IEEE third joint international conference on development and learning …, 2013 | 28 | 2013 |
| Accelerometry-enabled measurement of walking performance with a robotic exoskeleton: a pilot study L Lonini, N Shawen, K Scanlan, WZ Rymer, KP Kording, A Jayaraman Journal of NeuroEngineering and Rehabilitation 13, 1-10, 2016 | 25 | 2016 |
| Wearable sensors for Parkinson’s disease: which data are worth collecting for training symptom detection models. npj Digit L Lonini, A Dai, N Shawen, T Simuni, C Poon, L Shimanovich, ... Med 1 (1), 64.10, 2018 | 18 | 2018 |
| Automatic detection of spasticity from flexible wearable sensors L Lonini, N Shawen, R Ghaffari, J Rogers, A Jayarman Proceedings of the 2017 ACM International Joint Conference on Pervasive and …, 2017 | 16 | 2017 |
| Association of sleep with neurobehavioral impairments during inpatient rehabilitation after traumatic brain injury MB Maneyapanda, R Stork, B Ingraham, L Lonini, A Jayaraman, ... NeuroRehabilitation 43 (3), 319-325, 2018 | 14 | 2018 |
| Voodoo machine learning for clinical predictions. bioRxiv 059774 S Saeb, L Lonini, A Jayaraman, DC Mohr, KP Kording | 14 | 2016 |
Arun Jayaraman PT PhDProfessor, Northwestern University; Shirley Ryan Abilitylab/ Rehabilitation Institute ofE-mail confirmado em northwestern.edu