Goal: In this paper we investigated the use of smartphone sensors and Artificial Intelligence techniques for the automatic quantification of the MDS-UPDRS-Part III Leg Agility (LA) task, representative of lower limb bradykinesia. Methods: We collected inertial data from 93 PD subjects. Four expert neurologists provided clinical evaluations. We employed a novel Artificial Neural Network approach in order to get a continuous output, going beyond the MDS-UPDRS score discretization. Results: We found a Pearson correlation of 0.92 between algorithm output and average clinical score, compared to an inter-rater agreement index of 0.88. Furthermore, the classification error was less than 0.5 scale point in about 80% cases. Conclusions: We proposed an objective and reliable tool for the automatic quantification of the MDS-UPDRS Leg Agility task. In perspective, this tool is part of a larger monitoring program to be carried out during activities of daily living, and managed by the patients themselves.
Goal: In this paper we investigated the use of smartphone sensors and Artificial Intelligence techniques for the automatic quantification of the MDS-UPDRS-Part III Leg Agility (LA) task, representative of lower limb bradykinesia. Methods: We collected inertial data from 93 PD subjects. Four expert neurologists provided clinical evaluations. We employed a novel Artificial Neural Network approach in order to get a continuous output, going beyond the MDS-UPDRS score discretization. Results: We found a Pearson correlation of 0.92 between algorithm output and average clinical score, compared to an inter-rater agreement index of 0.88. Furthermore, the classification error was less than 0.5 scale point in about 80% cases. Conclusions: We proposed an objective and reliable tool for the automatic quantification of the MDS-UPDRS Leg Agility task. In perspective, this tool is part of a larger monitoring program to be carried out during activities of daily living, and managed by the patients themselves.
Entities:
Keywords:
Artificial neural networks; bradykinesia; leg agility; parkinson's disease; smartphone
Authors: Christopher Ornelas-Vences; Luis Pastor Sánchez-Fernández; Luis Alejandro Sánchez-Pérez; Juan Manuel Martínez-Hernández Journal: Med Biol Eng Comput Date: 2018-09-13 Impact factor: 2.602
Authors: Shyamal Patel; Konrad Lorincz; Richard Hughes; Nancy Huggins; John Growdon; David Standaert; Metin Akay; Jennifer Dy; Matt Welsh; Paolo Bonato Journal: IEEE Trans Inf Technol Biomed Date: 2009-10-20
Authors: Florian Lipsmeier; Kirsten I Taylor; Timothy Kilchenmann; Detlef Wolf; Alf Scotland; Jens Schjodt-Eriksen; Wei-Yi Cheng; Ignacio Fernandez-Garcia; Juliane Siebourg-Polster; Liping Jin; Jay Soto; Lynne Verselis; Frank Boess; Martin Koller; Michael Grundman; Andreas U Monsch; Ronald B Postuma; Anirvan Ghosh; Thomas Kremer; Christian Czech; Christian Gossens; Michael Lindemann Journal: Mov Disord Date: 2018-04-27 Impact factor: 10.338