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5 Fall-Risk Factors Measured by Medical PMDs

What is a Medical PMD and Who Are They Useful To?

Medical pressure measurement devices (Medical PMDs) are pressure sensitive technologies that have found a niche as modern gait assessment tools. PMDs may be single tiles or walkways and provide clinicians with data-rich analysis of gait parameters such as temporal measurements, spatial measurements, center of pressure (COP), and plantar pressures.

Medical PMDs are useful to medical professionals not just for rehabilitation and treatment, but also for monitoring conditions such as patient fall-risk. How so? Read on to learn about five fall-risk metrics that are indicative of fall risk and can measured by a medical PMD. 

5 Fall-Risk Factors Measured by Medical PMDs

1. Gait Velocity 

Gait velocity, or the speed at which someone walks, is a temporal  of gait associated with fall risk. The slower an elderly person is, the higher their risk for falling.  Research suggests that a gait speed below 1.0 m/s is a strong predictor of a fall. Any speed above 1 m/s reduces the risk, but as speed increases above 1.15 m/s, the reduction decreases.

A medical PMD that captures multiple steps can calculate gait velocity, which can in turn be used to gauge a patient’s level of fall risk.


2. Gait Rhythm 

Someone’s gait rhythm describes how well the phases of their gait cycle match typical proportions (stance phase is typically 60% of gait time, swing phase is typically 40%). Gait rhythm is usually determined by observing double support time and swing phase. Longer double support and shorter swing phase support are associated with a higher risk of falling. 

A medical PMD can measure the rhythm of a patient’s gait to provide clinicians with clues about their fall risk.

3. Gait Pressure 

Gait pressure, or the distribution of pressure under a patient’s foot while they walk, is another parameter of gait that is indicative of fall risk. Specifically, high foot pressures during gait are related to foot pain, which in turn is linked to a higher risk of falling. 

Medical PMDs are such valuable gait analysis tools because they provide plantar pressure measurements, to draw a complete picture of a patient’s mobility for clinicians.


4. Gait Variability 

Gait variability is the consistency of a person’s walk. Healthy gait is symmetrical and so the degree of variability of a person’s gait can be used to evaluate their fall risk. Research suggests that inconsistent walkers, or those with higher gait variability, are less stable and therefore more likely to fall. One study found that more specifically, increased variability in stride length and double support, indicate a less confident walker and contribute to a higher fall risk. 

Medical PMDs are capable of measuring variability not just in the temporal and spatial parameters of gait, but also in the pressure distribution during the gait cycle. This detailed analysis can ensure accurate measures of gait variability, and therefore, accurate fall risk assessment. 

5. Balance (Postural Sway) 

Postural sway is an objective measure of someone’s balance, and balance ability, and can differentiate between people who experience falls and those who do not. 

People tend to be able to stand more still with their eyes open than with their eyes closed. However, the ratio of sway between eyes closed and eyes open in elderly individuals with a higher risk of falling is lower than for elderly with lower fall risk. 

Medical PMDs can track the path of a patient’s center of pressure (COP) during both static and dynamic assessments- something nearly impossible to measure with the naked eye or with switch-technology instrumented walkways. This ‘sway’ can then be used to indicate a patient’s fall risk, even when issues are not obvious.

Objective Fall Risk Assessments Using the Stepscan System

Our Stepscan Fall Risk module provides detailed insights into a patient’s fall risk to help clinicians objectively assess the stability of patients aged 60 or older. Combining metrics from unobtrusive gait and balance assessments, our software summarizes a patient’s Fall Risk using the five research-supported KPIs mentioned above. 

We also offer easy-to-interpret reports, with the fall risk KPIs highlighted in green (indicating that the calculated value is within a healthy/normal range, yellow (indicating that the calculated value is at the fringe of healthy and should be monitored), or red (indicating that the calculated value is irregular or outside of a healthy range). 

Screenshot of KPIs on Fall Risk Report Summary

Stepscan Fall Risk assessments also calculate an overall Stability Scorea proprietary aggregate score calculated using the five fall-risk KPIs and which indicates a patient’s risk of falling within the next twelve months.

Screenshot of Stability Score on page one of a Fall Risk Summary

To learn more about the Stepscan Fall Risk module, connect with one of our Stepscan Product Specialists today.

If you are a clinician, comment below with how you currently calculate a patient’s fall risk. How would incorporating objective measures from a medical PMD impact your practice?

Works Cited and Additional Reading

Callisaya, Michele L., Leigh Blizzard, Michael D. Schmidt, Kara L. Martin, Jennifer L. McGinley, Lauren M. Sanders, and Velandai K. Srikanth. 2011. “Gait, gait variability and the risk of multiple incident falls in older people: a population-based study.” Age and Ageing 40, no. 4 (05): 481-487. 10.1093/ageing/afr055.

Hausdorff, J. M., D. A. Rios, and H. K. Edelberg. 2001. “Gait variability and fall risk in community-living older adults: a 1-year prospective study.” Archives of physical medicine and rehabilitation 82, no. 8 (08): 1050-1056. 10.1053/apmr.2001.24893.

Howcroft, Jennifer, Edward D. Lemaire, Jonathan Kofman, and William E. McIlroy. 2017. “Elderly fall risk prediction using static posturography.” PLOS ONE 12, no. 2 (02): e0172398. 10.1371.

Kyrdalen, Ingebjørg L., Pernille Thingstad , Leiv Sandvik, Heidi Ormstad. 2018. “Associations between gait speed and well-known fall risk factors among community-dwelling older adults.” Physiotherapy Research International 2019 Jan; 24(1): e1743. doi: 10.1002/pri.1743. Epub 2018 Sep 10. PMID: 30198603.

Maki, B. E. 1997. “Gait changes in older adults: predictors of falls or indicators of fear?” Journal of the American Geriatrics Society 45, no. 3 (03): 313-320. DOI: 10.1111/j.1532-5415.1997.tb00946.x. 

Mickle, Karen J., Bridget J. Munro, Stephen R. Lord, Hylton B. Menz, and Julie R. Steele. 2010. “Foo pain, plantar pressures, and falls in older people: a prospective study.” Journal of the American Geriatrics Society 58, no. 10 (11): 1936-1940. 10.1111/j.1532-5415.2010.03061.x. 

About Crystal Trevors

Crystal is the founder and owner of Stepscan Technologies Inc. She holds a Bachelor of Science from the University of New Brunswick, a Master of Science in Biology from the University of Prince Edward Island, and a Master in Business Administration from the University of Guelph. Her business and research interests include corporate performance management and reporting, process improvement and operational efficiencies. Operating Stepscan is a dream come true for her, allowing her to combine her love of biology, research and business, every day.

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