Given the increased use of wearable devices, such as smart watches, which are able to monitor a broad range of physiological activities, it makes sense that actigraphy is a growing trend in clinical trials. Actigraphy is a non-invasive way to monitor human rest and activity. Some use cases in clinical trials are more obvious, such as in the study of Parkinson's disease, where a wearable sensor can measure tremors in order to track the ON and OFF activity cycles indicative of levodopa treatment. But the uses of actigraphy are much wider, including everything from behavioral, to CNS, to respiratory, circulatory and oncology-related conditions.
Broadly, actigraphy can be used to evaluate step counts, total sleep time per sleep period, activity intensity and number of nighttime awakenings—and, importantly, daily measures of activity, a measure common to many clinical trials, including Alzheimer's disease, COPD and multiple sclerosis. In pre-clinical trials, actigraphy data can be used to help screen potential patient populations. In early drug development, actigraphy may be used to collect physiological data to identify early safety signals and to inform dosing adjustments. Later-stage clinical development can leverage actigraphy to create novel endpoints in multiple disease areas. Unlike taking data at a single clinic visit, which creates discrete data points, wearables and similar monitors collect a range of data that can provide useful clinical and physiological insights.
Types of Measurements
Most wearable actigraphy devices on the market utilize a 3-axial accelerometer, which can measure movements in all three axes, X, Y and Z. Some devices also can detect the intensity of movement along each axis, which can allow for setting thresholds to differentiate between voluntary or non-voluntary movements, sleep movement, or can be used to classify activity into different categories, such as mild, moderate and strenuous. Many devices measure heart rate and rhythm, as well as oxygen saturation.
In clinical trials actigraphy measurements can be leveraged for a variety of uses. They include efficacy endpoints, an extension of clinical assessments, direct measures for clinical endpoints, and to support corollary measures and derived measures.
Wearable devices have a significant advantage in providing real-time insight in a way that is both patient-centric and research-compliant. They can support, and in some cases replace, traditional methods of measurement. In terms of patient-centricity, the data is collected at an in-home setting: this is likely to be more accessible, non-invasive, simple, affordable, accurate, and well-accepted by the patient in comparison with in-clinic measurements. The typical wearable device is convenient, can be worn on wrist or waist and used during all daily living activities, such as sleeping, showering, and exercising.
Of course, one of the largest advantages is that these devices collect data in real-time and over a continuum, rather than at a single period during a site visit. This form of data collection offers dense data that may help identify early safety issues, appropriate dosages, and more. They also can measure data to a more sensitive and specific degree than traditional tools and can enable faster and more objective readouts, particularly in areas that are traditionally subjective, such as pain or fatigue.
Many wearable devices used in actigraphy collection have corresponding software in which the data are integrated into specific pre-defined measurements, and often the provider has validated the algorithms already. This can minimize the need to import raw accelerometry data into a database, as it is designed to be delivered as integrated data. Some devices will require external software to integrate the data. As a result, researchers will need to decide ahead of time what kind of data integration they want and if the device-software package provides the appropriate integration.
This type and quantity of data are changing how health information is collected, processed and visualized, and have the potential to improve data volume, accuracy and efficiency. This creates opportunities to improve the speed with which new treatments reach patients, the degree of efficacy that treatments can offer, and the ability of organizations to fine-tune drug development budgets.
Recommendations for Use
As with any clinical trial, an important decision for choosing a wearable for actigraphy measurements is predicated upon understanding the scientific question and nature of the study being conducted. What parameters are needed? Does the research need only actigraphy, or also sleep and heart rate?
In addition, do you need to measure the quality or intensity of an activity as opposed to just the time in motion? Will the device need a screen so the patient can self-monitor, or is it only being used to collect data? Do you wish the device to be able to send notifications and reminders to the patient? Is it necessary for the device to note if it is being worn? And what kind of conditions, such as ambient light, are needed? All of these considerations make it possible to accurately determine the appropriate expectations for the actigraphy data, including the type of measurements and the length of time it will be collected.
Then, make it a mandatory part of the study protocol, and choose a device that best fits the study objectives, including battery life, memory capacity and ease-of-use.
Spend time thinking about and developing patient-engagement strategies for physical activity, and provide training and support not only for the patients, but also for the investigators and clinical research associates.
And, as mentioned above, wearables create large amounts of very dense data. Consider the challenges of collecting and integrating large amounts of actigraphy data, such via remote data collecting using a platform such as Koneksa's, which can transfer large column-wise datasets that traditional CRF and SDTM models don't natively support.
A clinical trial is a data collection and management challenge, and wearables offer convenient, affordable and effective ways to generate and integrate vast amounts of data on a broad range of actigraphy measures. This real-time insight is both patient-centric and research-compliant, and can support, and in some cases replace, traditional measurement methods. The use of wearables has been an enormous boon to clinical trials in general — it is now possible to gather far more data, more often, more objectively, and more easily than ever before, and, with the appropriate choice, broadly expedite clinical trials utilizing actigraphy measurements.