Klassen, Bryan T

Assessing balance is crucial in neurological rehabilitation, yet while wearable sensors enable real-world monitoring, identifying reliable digital biomarkers remains challenging. This study utilized a high-fidelity instrumented walkway to determine which gait parameters best predict balance impairment, providing robust targets for future wearable applications. We analyzed 49 steady-state gait metrics from 140 individuals with diverse neurological conditions. Using statistical analysis and machine learning, we evaluated these parameters against objective force plate sway scores and clinical fall-history labels. Group analysis identified 16 parameters significantly distinguishing fallers from non-fallers, and a neural network classified fallers with an area under the curve of 0.75. Across all analytical approaches, overall gait variability, e.g., Stride Width S.D. and the Gait Variability Index, emerged as a universal predictor of balance impairment and fall risk. Furthermore, while traditional linear models emphasized spatial postural control, machine learning classification uniquely identified inter-limb asymmetry as a premier driver of fall prediction. These findings indicate that instrumented gait analysis effectively identifies digital biomarkers for balance deficits. Isolating these specific metrics provides a clear blueprint for meaningful metrics required for continuous objective monitoring and future development of personalized, adaptive rehabilitation strategies.

BACKGROUND AND OBJECTIVES: Stereotactic procedures are used to manage a diverse set of patients across a variety of clinical contexts. The stereotactic devices and software used in these procedures vary between surgeons, but the fundamental principles that constitute safe and accurate execution do not. The aim of this work is to describe these principles to equip readers with a generalizable knowledge base to execute and understand stereotactic procedures. METHODS: A combination of a review of the literature and empirical experience from several experienced surgeons led to the creation of this work. Thus, this work is descriptive and qualitative by nature, and the literature is used to support instead of generate the ideas of this framework. RESULTS: The principles detailed in this work are categorized based on 5 clinical domains: imaging, registration, mechanical accuracy, target planning and adjustment, and trajectory planning and adjustment. Illustrations and tables are used throughout to convey the concepts in an efficient manner. CONCLUSION: Stereotactic procedures are complex, requiring a thorough understanding of each step of the workflow. The concepts described in this work enable functional neurosurgeons with the fundamental knowledge necessary to provide optimal patient care.

We studied movement-associated spectral changes in human motor thalamus and observed focal increases in broadband power with movement. This biomarker may be used as a tool for intraoperative functional mapping, DBS targeting, and closed-loop device control.