Balance testing is widely used across diverse populations, such as older adults to assess fall risk and individuals with neurological conditions, including stroke, Parkinson’s disease, and peripheral neuropathy.

Traditionally, balance is determined using functional assessments like the Berg Balance Scale, which are simple, cost-effective, and quick to administer. While these clinical tests are practical, they are often subjective and may lack the precision needed to detect subtle changes in balance performance, limiting their usefulness in tracking progress or deterioration over time (1).

By integrating wearable sensors into functional balance assessments, such as the one-leg stance test, researchers can achieve more precise, sensitive, and comprehensive evaluations of balance in clinical settings (1).

The Single Leg Stance Test

The Single Leg Stance Test report provides several qualitative and quantitative outcome parameters to determine balance in a research setting:

Balance Point & Sway Area (Fig-1):

The Balance Point displays the center of pressure (COP) of the standing leg’s foot. It represents the distribution of weight across the foot, showing whether it is shifted toward the forefoot, hindfoot, medially, or laterally. The Sway Area is defined as the size of an ellipse encompassing 95% of the COP data points during the balance phase. This measurement reflects the stability of the foot’s contact with the ground, with a smaller Sway Area indicating greater stability and better control. Both outcomes are also given as numeric values: the Balance Point in longitudinal and transversal direction is normalized by sensor insole length, with the hindfoot and lateral side starting with 0, the forefoot and medial side ending with 1, respectively. In this example, the Sway Area on the left is noticeably larger compared to the right, indicating a significant difference in stability between the two sides.

An illustration of balance point distribution and sway area data from a single leg stance test, showing a larger sway area on the left side.
Fig-1: Visualizing Balance Point and Sway Area with sensor insoles.

Balance Progression (Fig-2, left):

The Balance Progression shows the traveling velocity of the balancing foot’s COP as a measure for balance development over time. Here, the deflections on the left side are greater than on the right.

COP Path Length & COP Velocity (Fig-2, right):

COP Path Length and COP Velocity relate to the overall travel length and the mean velocity of the COP, respectively. In addition to the Sway Area and Balance Progression, the COP Path Length and COP Velocity are also significantly greater on the left side than on the right.

A graphical comparison of balance progression, COP path length, and velocity, highlighting differences between the left and right sides during a balance test.
Fig-2: Further COP-related metrics are Balance Progression, COP Path Length and COP Velocity.

Sensor insoles for balance testing in clinical research

Balance evaluations in research are often conducted using functional assessments, such as the Berg Balance Scale.

Conversely, the introduction of sensor insoles represents a new approach to balance testing, offering significant advancements for clinical research. Moticon’s Sensor Insoles offer an affordable, valid, and reliable (2) tool for gaining in-depth insights into the biomechanics of balance.

By combining force measurements with pressure distribution, they enable researchers to gather detailed metrics related to COP. They measure key balance factors, such as Sway Area and COP Path Length, allowing for a detailed analysis of a patient’s balance abilities beyond subjective evaluation.

The wireless, fully integrated design of the sensor insoles allows tests to be conducted in clinical settings, without the need for a sophisticated lab. Additionally, the non-intrusive nature of the sensor insoles ensures that patients are not biased during testing.

Literature

  1. Mancini M, Horak FB. The relevance of clinical balance assessment tools to differentiate balance deficits. Eur J Phys Rehabil Med. 2010 Jun;46(2):239-48. PMID: 20485226; PMCID: PMC3033730.
  2. Cramer LA, Wimmer MA, Malloy P, O’Keefe JA, Knowlton CB, Ferrigno C. Validity and Reliability of the Insole3 Instrumented Shoe Insole for Ground Reaction Force Measurement during Walking and Running. Sensors (Basel). 2022 Mar 11;22(6):2203. doi: 10.3390/s22062203. PMID: 35336374; PMCID: PMC8951440.

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