Balance testing is widely used in the clinical context across diverse populations to assess risk of fall. Examples are older adults with gait instabilities, individuals with neurological conditions, including stroke, Parkinson’s disease, as well as 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 motion 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) while maintaining a time-efficient workflow.
Information
Integrating wearable motion sensors in the assessment of patients’ balancing abilities allows objective quantification of important outcome measures.
The Single Leg Stance Test
The Single Leg Stance Test instrumented with sensor insoles provides several qualitative and quantitative outcome parameters to determine balance in a research setting.
Balance Point & Sway Area
The Balance Point displays the center of pressure (COP) of the standing leg’s foot, representing 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 and width, with the hindfoot and lateral side starting with 0, the forefoot and medial side ending with 1, respectively. The dataset shown in Fig-1 indicates a significant difference in stability on the left side with the left Sway Area noticeably larger compared to the right.
Balance Progression
The Balance Progression shows the traveling velocity of the balancing foot’s COP as a measure for balance development over time. Greater deflections represent more movement of the COP and indicate poorer stability. Fig-2 left displays the Balance Progression of the same trial as the data in Fig-1. The deflections on the left side are greater than on the right, which coincides with the larger Sway Area on the left.
COP Path Length & COP Velocity
COP Path Length and COP Velocity relate to the overall travel length and mean velocity of the COP, respectively. Higher values for COP Path Length and COP Velocity refer to less stability of the balancing foot. Fig-2 right shows that in addition to Sway Area and Balance Progression, the COP Path Length and COP Velocity are also significantly greater on the left side than on the right which suggests impaired balance on the left.
Recent research shows that parameters like Sway, COP Path Length, and COP Velocity can predict fall risk in older adults (2), highlighting the value of sensor-based assessments in both patient care and research.
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 (3) tool for gaining in-depth insights into the biomechanics of balance.Â
By combining force measurements with pressure distribution, they enable researchers to gather a variety of metrics related to balance and mobility. For instance, 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
- 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.
- Pizzigalli L, Micheletti Cremasco M, Mulasso A, Rainoldi A. The contribution of postural balance analysis in older adult fallers: A narrative review. J Bodyw Mov Ther. 2016 Apr;20(2):409-17. doi: 10.1016/j.jbmt.2015.12.008. Epub 2015 Dec 18. PMID: 27210860.
- 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.
