Prediction of Freezing of Gait in Parkinson's From Physiological Wearables: An Exploratory Study

Abstract

Freezing of gait (FoG) is a common gait impairment among patients with advanced Parkinson's disease. FoG is associated with falls and negatively impacts the patient's quality of life. Wearable systems that detect FoG in real time have been developed to help patients resume walking by means of rhythmic cueing. Current methods focus on detection, which require FoG events to happen first, while their prediction opens the road to preemptive cueing, which might help subjects to avoid freeze altogether. We analyzed electrocardiography (ECG) and skin-conductance (SC) data from 11 subjects who experience FoG in daily life, and found statistically significant changes in ECG and SC data just before the FoG episodes, compared to normal walking. Based on these findings, we developed an anomaly-based algorithm for predicting gait freeze from relevant SC features. We were able to predict 71.3% from 184 FoG with an average of 4.2 s before a freeze episode happened. Our findings enable the possibility of wearable systems, which predict with few seconds before an upcoming FoG from SC, and start external cues to help the user avoid the gait freeze.

Clinical and methodological challenges for assessing freezing of gait: Future perspectives

“…In order for this online cueing modality to work, a “pre‐freezing phase” needs to be characterized reliably. A few studies have investigated the presence of a pre‐FOG phase in the laboratory using different apporaches, including motion analysis systems, surface EMG, electrocardiography, and, more recently, with mobile imaging such as ambulatory EEG, functional near‐infrared spectroscopy, and wearable inertial sensors . Nieuwboer and colleagues found signs of deterioration of the gait pattern as early as three steps before a FOG episode, reflected by a decreased stride length and increased or stable cadence .…”

“…Only few reports have characterized the pre‐FOG phase with inertial sensors . The results were promising, particularly in a study of 11 subjects with PD and FOG where information was combined from accelerometers and gyroscopes.…”

A clinical view on the development of technology-based tools in managing Parkinson's disease

“…Therapeutic strategies include pharmacological (mainly dopaminergic, but also other drugs) and nonpharmacological interventions (e.g., DBS and cueing strategies) that have been shown to be effective treatment options, but these options are not equally effective for all patients affected by freezing. Studies using technology‐based tools to detect and evaluate FOG in an unsupervised environment indicate that the sensitivity and specificity justify further research on this topic . The aim is to include tools to support the rapid identification of responders and nonresponders within a selected treatment regimen and to even use these tools in closed‐loop systems to treat acute episodes.…”

Assessing Motor Fluctuations in Parkinson’s Disease Patients Based on a Single Inertial Sensor

“…More concretely, these works mainly rely on the use of inertial sensors, although there are other less extended alternatives, as the use of sEMG [25,26,27,28] or another physiological measure [29]. The majority of these research studies have employed wearable sensors to study specific PD symptoms such as FOG [30,31,32], dyskinesia [33,34,35,36] and bradykinesia [18,19,22,37,38,39]; thus, the aim was detecting the presence or severity of a certain symptom.…”