Assessing upper limb function in multiple sclerosis using an engineered glove.

Area of Science:

• Neurology
• Rehabilitation Medicine
• Biomedical Engineering

Background:

• Upper limb function is crucial in multiple sclerosis (MS), particularly for progressive forms impacting mobility.
• Sensor-engineered gloves quantitatively assess finger opposition, aiding upper limb disability evaluation in MS.
• Existing methods like the Nine-Hole Peg Test (9HPT) are standard but may not capture the full spectrum of disability.

Purpose of the Study:

• Confirm the association between glove-derived metrics and established MS disability measures in a larger cohort.
• Evaluate correlations between glove data, quantitative MRI, and Quality of Life (QoL) indicators.
• Determine if glove-derived variables offer superior assessment of upper limb function in MS compared to the 9HPT.

Main Methods:

• Sixty-five MS patients on stable treatment were assessed using sensor gloves, clinical exams (EDSS, SDMT, T25FW, 9HPT), MRI, and QoL questionnaires.
• Spearman's rank correlation coefficient was used to analyze relationships between glove variables and clinical, MRI, and QoL data.

Main Results:

• Glove variables distinguished between relapsing-remitting and progressive MS.
• Correlations between the 9HPT and clinical variables were similar or slightly higher than glove-derived variables.
• Glove metrics demonstrated stronger correlations with the physical component of QoL and significant correlations with the mental component, unlike the 9HPT.

Conclusions:

• Sensor-engineered gloves provide valuable, quantitative data on upper limb function in MS.
• These gloves show potential advantages over the 9HPT, particularly in relation to QoL measures.
• Further longitudinal studies are recommended to assess the sensitivity to change of glove-derived variables in MS.