The Nonmotor Features of Parkinson's Disease

Touchscreen typing-pattern analysis for detecting fine motor skills decline in early-stage Parkinson's disease

Parkinson’s disease (PD) is a degenerative movement disorder causing progressive disability that severely affects patients’ quality of life. While early treatment can produce significant benefits for patients, the mildness of many early signs combined with the lack of accessible high-frequency monitoring tools may delay clinical diagnosis. To meet this need, user interaction data from consumer technologies have recently been exploited towards unsupervised screening for PD symptoms in daily life. Similarly, this work proposes a method for detecting fine motor skills decline in early PD patients via analysis of patterns emerging from finger interaction with touchscreen smartphones during natural typing. Our approach relies on low-/higher-order statistical features of keystrokes timing and pressure variables, computed from short typing sessions. Features are fed into a two-stage multi-model classification pipeline that reaches a decision on the subject’s status (PD patient/control) by gradually fusing prediction probabilities obtained for individual typing sessions and keystroke variables. This method achieved an AUC = 0.92 and 0.82/0.81 sensitivity/specificity (matched groups of 18 early PD patients/15 controls) with discriminant features plausibly correlating with clinical scores of relevant PD motor symptoms. These findings suggest an improvement over similar approaches, thereby constituting a further step towards unobtrusive early PD detection from routine activities.

Sleep quality is associated with the severity of clinical symptoms in Parkinson's disease

Sleep disorders are very common in Parkinson's disease (PD), being associated with several other conditions, mainly psychiatric disorders. The present study was designed to assess sleep quality in Brazilian patients with PD and to evaluate whether sleep changes are associated with clinical variables, especially neuropsychiatric symptoms in PD. Patients diagnosed with PD were subjected to a comprehensive clinical evaluation that included the assessment of motor, cognitive and psychiatric symptoms. Our study showed that sleep complaints are frequent in PD and worse sleep quality is associated with depressive and anxious symptoms, poorer cognitive performance and greater severity of PD symptoms. In the multivariate analysis, older age, greater severity of anxiety and PD remained as significant predictors of worse sleep quality. In conclusion, sleep complaints, depressive and anxiety symptoms are frequent in PD patients. Older age, disease severity and anxiety symptoms are significant predictors of poorer sleep quality in PD patients.