Health conscious Americans are using a variety of new tools to help them measure their fitness. Activity monitors, including Fitbit, Jawbone UP, and Nike Fuelband, keep track of heartbeats, body temperature, the number of steps a user takes, and other data. Some smartwatches record similar data. Measurements of time and distance (assisted by GPS components) allow fitness monitors to compute the speed at which the person wearing the device has been walking or running.
Fitness technology users often have the option to upload the information collected by their devices to an online database. That allows them to keep track of their activity over time. It also permits a comparison of the user’s information to a broad group of people who share similar characteristics (such as age and gender).
The advent of fitness technology has given rise to a new breed of experts. Statisticians are using fitness monitoring data to compare individuals to larger populations. In some cases, they are using data gained from technology users when they testify as expert witnesses.
Experts in Activity Analysis
The first court case involving the expert analysis of data collected from a Fitbit device took place in Canada. A personal injury plaintiff who was injured when she was working as a fitness trainer used expert testimony to establish that her activity levels were lower than average for a person of her age and profession.
Of course, a plaintiff who is malingering might deliberately engage in lessened activity while wearing the Fitbit device. The expert’s data analysis might therefore shed limited light on whether an individual user’s data has been manipulated. The Canadian court presumably left that issue for the jury to resolve.
Whether an activity data analysis would be permitted in an American court would likely depend on whether the party seeking its admission can satisfy the standard for expert evidence that applies in that court. In states that adhere to the Daubert standard, the party would need to establish that the expert’s testimony is based on the application of a reliable methodology to reliable data. The reliability of data that can be manipulated by the person wearing a monitor might be difficult to prove.
While plaintiffs might have trouble using an activity analysis to prove their injury claims, activity data might be a boon to insurance companies that seek to expose fraudulent claims. A plaintiff who claims a serious injury might have difficulty explaining an analysis of Fitbit data showing that the plaintiff is more active than an average person of a similar age. Activity data might also show that a plaintiff who claims to be disabled goes jogging every day. Of course, a savvy individual who wants to make a false insurance claim might know better than to wear a smartwatch or to upload Fitbit information to a database.
As courts increasingly become aware of the perils of eyewitness identification, they may see technology as a means to increase the reliability of evidence that juries consider. Yet raw data is nearly always subject to human interpretation provided by expert witnesses.
As one commentator notes, courts should understand that a “data-driven regime of truth” can be just as unreliable as eyewitness testimony. Some monitoring devices record arm movements as walking when the wearer is sitting in a chair while writing or eating. Others fail to record cycling as an activity. The algorithms that data analysis experts use to interpret the raw data may be flawed, while the data uploaded by people who use fitness trackers may not be representative of the population as a while.
Courts that apply a Daubert rule will presumably examine the reliability of data assessments made by expert analysts. Juries may also hear testimony from competing experts pointing out the problematic nature of data-driven evidence. In the end, however, expert opinions based on fitness tracking technology is likely to become increasingly common in the courtroom.