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Sleep is essential for overall well-being, but for people with knee osteoarthritis (KOA) it can be a major challenge, as they often suffer from sleep disturbances and pain, which can adversely affect their sleep. Indeed, tracking sleep accurately can be very tricky. That is why sleep specialists and studies use a device called Polysomnography (PSG). It is a complex sleep monitoring method made of different sensors that track heart rate, brain waves, skin temperature, blood oxygen levels, muscle activity (and other parameters) to determine how well (or poorly) people sleep. Over the years, portable PSGs were developed to decrease the burden of having to sleep a night in a laboratory rather than in the comfort of your own home. Nevertheless, these devices remain uncomfortable with lots of cables and sensors running around. In addition, the process is often time-consuming and requires the presence of a specialist. A relatively new option, which is also cheaper than PSG are consumer wearable devices such as Fitbit ® Sense (FS). They are more convenient, less invasive (a tiny watch on your wrist) and accessible (your local technology store probably has few models already) alternatives for sleep quality tracking. Besides, they do not require any specific action by the user or the presence of a specialist. The problem is that their performance, when compared to PSG, is often unknown. Collecting and analyzing data from them might lead to wrong interpretations and mislead treatment. Therefore, the aim of this study was to explore how well the FS smartwatch can measure some sleep quantity and continuity parameters compared to PSG on people who have both knee osteoarthritis and sleep disturbances. 16 individuals diagnosed with KOA and coexisting sleep disturbances were included in the study, as part of a project examining the added value of cognitive behavioral therapy for insomnia in KOA (PREMEO trial) in the Leuven & Brussels region, Belgium. They underwent a one-night PSG assessment scheduled and carried out in their home. In addition, they were also given a FS to wear that night before returning it with the PSG equipment. Our study showed that on one hand FS can be a viable option against PSG in some of the sleep parameters. Specifically, FS and PSG showed a high level of agreement when tracking how long people slept. When tracking how long it took them to fall asleep, FS showed promising results, but its performance was very much influenced by what was the reason (underlying pathology) for the subject’s sleep problem. However, when it came to tracking how efficient sleep was (meaning how much time people slept in all the time they laid down in bed) and how much time they spent awake during the night, FS tended to overestimate and underestimate them respectively. On the other hand, since wearable devices are always evolving (software updates, new versions), FS performance might change in the future. Therefore, scientists and therapists should not make assumptions about its performance without studies backing up their claims, or at least interpret the findings with caution.