Technologies for identification of prodromal movement disorder phases and at-risk individuals

Timely identification of individuals at risk for developing neurodegenerative conditions is an unmet need which would enable us to initiate treatment at an earlier stage and potentially slowing down disease progression or reducing the risk of phenoconversion. Currently, the identification of prodromal stages remains challenging due to the lack of uniform criteria for the prodromal stage of neurodegenerative conditions and suboptimal symptom identification due to limitations in diary and scale-based assessments. Here, remote and wearable technology might offer a new way forward. In this chapter we summarize the currently available evidence for technology based identification of both motor and nonmotor features in neurodegenerative conditions, in particular Parkinson’s (PD) and Huntington’s disease (HD) and spinocerebellar ataxias (SCA). Although limited in absolute number, most studies have focused on prodromal and premanifest motor features, showing e.g., reduced arm swing and changes in gait parameters in prodromal individuals at risk for PD, as well as gait and balance abnormalities in premanifest HD and SCA gene mutation carriers. Nonmotor features, on the other hand, remain understudied with only limited evidence for the identification of cognitive changes in premanifest HD gene mutation carriers. Further efforts, especially in the field of nonmotor features, are needed before such technology could be used in clinical practice to identify individuals at risk for or in a premanifest stage of neurodegenerative conditions.