12/11/2022 0 Comments Fit bits and sleep disorder![]() ![]() In this article, we explain what your sleep data points mean and how to use them to your benefit.ĭuring deep sleep, your breathing rate and heart rate slow down even more and your body wholly relaxes. The information available to you depends on the device you have, but most sleep trackers collect a variety of data points. OK, maybe not superhuman (unless you're an expert biohacker), but you'll still feel dang good. If you utilize that data, you can manipulate your diet, workout routine, stress management tactics and other factors to become superhuman. But tracking your sleep can reveal a wealth of information about your health that you may have been totally oblivious to before. When you first look at your sleep tracker data, all those numbers and graphs may feel dizzying. If you have a smartwatch, fitness tracker or even a health app on your phone, you can gather useful sleep data from the comfort of your own bed, ranging from heart rate to breathing rate and sleep stage percentages. These days, you don't have to go into a sleep clinic to learn key details about your sleep. It was also limited by the fact that participants used study-specific mobile phones and the data many not have reflected personal mobile phone use patterns, according to researchers.Ĭurrently the researchers are running follow-up studies to determine whether the same passive sensing approach can be used to identify complications following cancer surgery.This story is part of Health by the Numbers, CNET's deep dive into how we quantify health. ![]() The study was only four weeks long, which was a limitation, according to the authors. ![]() This suggests that future passive sensing research focused on symptoms could consider relying only on the features derived from the phone accelerometer and GPS as well as information about duration of phone and app usage and battery charges.” “In particular, features related to mobility and activity and phone usage patterns yielded the most accurate models. “Results of device-specific feature selection indicate that features from mobile phone sensors were more valuable in symptom estimation than Fitbit features,” authors in the study wrote. ![]() They found that the phone activity had a higher correlation to patients’ symptom burdens than Fitbit recorded activity. Researchers also examined the performance models they built with data from each device. The number of sedentary bouts and time spent on the smartphone strongly correlated to higher symptom severity. Using this algorithm researchers found an 88 percent accuracy between patient-reported symptom burdens and the correlated mobile and Fitbit features. Researchers looked at the sensor and symptom data and discovered a number of mobile and Fitbit features were correlated to patient-reported symptom burden scores, according to the study. The scores were centered on individual patients means and categorized into low, average and high symptom burden days, according to the study. Severity ratings were totaled to create a symptom burden score for each day. Every day patients rated the severity of 12 common chemotherapy symptoms. #Fit bits and sleep disorder android#Each of the participants carried an Android phone provided by the study and wore a Fitbit for the duration of the 4-week study. The study was made up of 14 patients undergoing chemotherapy for gastrointestinal cancer. The study set out to look for links between these symptoms and certain mobile and Fitbit activities. Other symptoms like nausea and pain are also common but can fluctuate with each chemo cycle, according to researchers. Symptoms such as fatigue and sleep disturbances are common among chemotherapy patients. "Collecting these objective behavioral measures from smartphone sensors requires no additional effort from patients, and they could prove beneficial for long-term monitoring of those undergoing arduous cancer treatments or those with other chronic illnesses." "We found that on days when the patients reported worse-than-average symptoms, they tended to spend more time being sedentary, moved the phone more slowly, and spent more minutes using apps on the phone,” Carissa Low, professor of medicine and psychology at the University of Pittsburgh, and lead author of the study, said in a statement. A small study published in the Journal of Medical Internet Research found that passive sensor data collected from smartphones and Fitbits could be linked to the severity of symptoms cancer patients experienced during their chemotherapy treatment. ![]()
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