From the Guidelines
Smartwatches can be used as a predictor of gait abnormalities, but their use should be considered complementary to traditional clinical assessments rather than a replacement. Modern smartwatches equipped with accelerometers and gyroscopes can collect data on walking patterns, stride length, and balance, which are key components of gait analysis 1. This technology offers the advantage of continuous, real-world monitoring outside of clinical settings. To implement smartwatch-based gait prediction, users should wear their devices consistently during daily activities. Most smartwatches automatically collect movement data, but specific gait analysis apps may need to be installed for more detailed insights. Users should consult with healthcare providers to interpret the data and integrate it into their overall health assessment. The potential of smartwatches in gait prediction lies in their ability to detect subtle changes over time that might indicate increased fall risk or the progression of neurological conditions like Parkinson's disease 1. The continuous nature of data collection allows for more comprehensive analysis compared to occasional clinical visits. However, it's essential to consider the limitations and potential biases of smartwatch-based gait analysis, such as variations in watch placement, user compliance, and individual gait characteristics 1. Therefore, smartwatch gait data should be used as a supplementary tool to enhance clinical decision-making rather than as a standalone diagnostic method. Some key considerations for the validation of consumer wearables and smartphones for gait prediction include:
- Target population: The validation protocol should include a diverse range of participants, including those with typical and atypical gait characteristics 1.
- Criterion measure: A reference test with high accuracy, such as video camera analysis, should be used to validate the smartwatch data 1.
- Index measure: The smartwatch should be placed in an ecological body location, and the data should be collected in a manner that does not affect gait patterns or activities of daily living 1.
- Testing conditions: The validation protocol should include a range of activities, such as walking, running, and household tasks, to capture the variability of real-world gait patterns 1.
From the Research
Gait Abnormalities Prediction Using Smartwatches
- The use of wearable electronic devices, such as smartwatches, for predicting gait abnormalities has been explored in various studies 2, 3, 4.
- A narrative review of clinical feasibility found that wearable gait measurement devices can be used for falls-risk assessment in neurological and non-neurological populations, with inertial measurement units (IMU) displaying competency in obtaining and interpreting gait metrics relevant to falls risk 2.
- However, the accuracy of commercial smartwatches for monitoring step counting may be reduced in patients with Parkinson's disease (PD) and further influenced by the pharmacological condition and placement of the device 3.
- Gait analysis using wearable sensors has been found to be a valuable tool for clinical applications, including diagnosing and monitoring disease progression in neurological populations 4, 5.
- A study on the validity and reliability of a smartphone IMU-based gait speed measurement found that it can be a viable and convenient method for measuring gait speed outside of laboratory and clinical settings, with potential applications in various settings and populations 6.
Key Findings
- Wearable devices, including smartwatches, can be used to predict gait abnormalities and falls risk in various populations 2, 3, 4.
- The accuracy of these devices may be influenced by factors such as pharmacological condition, device placement, and walking conditions 3, 6.
- Gait analysis using wearable sensors can provide valuable insights into disease progression and mobility in neurological populations 4, 5.
- Further research is needed to fine-tune the use of wearable devices for gait analysis and to explore their potential applications in various settings and populations 6.