Quantified-Self for Obesity: Physical Activity Behaviour Sensing to Improve

Health OutcomesDavid TAYLORa1, Jennifer MURPHYa, Mian AHMADa, Sanjay PURKAYASTHAb,

Samantha SCHOLTZc, Ramin RAMEZANId, Ivaylo VLAEVe, Alexandra I.F. BLAKEMOREb and Ara DARZIa

a Department of Surgery, Cancer and Investigative Medicine, Imperial College London

b Division of Diabetes, Endocrinology, and Metabolism, Imperial College London

cDepartment of Investigative Medicine, Imperial College LondondWireless Health Institute, University of California, Los Angeles

eBehavioural Science Group, Warwick Business School, University of Warwick

Abstract. Physical activity levels in bariatric patients have not been well documented, despite their importance in maintaining weight loss following surgery. This study investigated the feasibility of tracking physical activity using a smartphone app with minimal user interaction. Thus far, we have obtained good quality data from 255 patients at various points in their weight loss journey. Preliminary analyses indicate little change in physical activity levels following surgery with pre-surgery patients reaching an average of 16 minutes per day and post-surgery patients achieving a daily average of 21 minutes. Further analyses using machine-learning techniques will be conducted to determine whether physical activity is a critical factor in distinguishing between successful and unsuccessful weight loss outcomes and in the resolution of comorbid conditions in patients with similar clinical profiles.

Keywords. Quantified-self; Mobile health technologies; Physical activity; Bariatric; Weight-loss; Machine-learning

1. Introduction

While bariatric surgery is the most effective therapeutic approach to obesity, 10-30% of patients experience sub-optimal weight loss[1;2;3]. Physical activity is effective for long-term weight loss maintenance following calorie restriction diets but there is a lack of research on its effects on weight loss maintenance following bariatric surgery[4]. Previous research objectively measuring physical activity has shown that while there is a wide range of activity levels in bariatric patients, the majority achieve significantly less than the recommended 150min/week physical activity guidelines before- and up to 3 years after surgery [5;6]. However, these studies have been limited to comparisons of physical activity within a short time window of 1 week before surgery and 1 week at

1 Corresponding Author. Department of Surgery, Cancer and Investigative Medicine,Imperial College London, St Mary's Hospital, 10th Floor QEQM Building, South Wharf Road, London, W2 1NY, ditaylor@imperial.ac.uk

one year post-surgery. It is important to gain a better understanding of physical activity trajectories in this group over time and to ascertain whether increased physical activity is associated with better weight loss outcomes and resolution of comorbid conditions.

2. Aims

The primary aim of this study is to assess the feasibility of continuously tracking physical activity in bariatric patients throughout their weight loss journey using only their smartphones with minimal user interaction required. We aim to characterize the physical activity profile of bariatric patients and to determine whether physical activity is a critical factor in distinguishing between successful and unsuccessful weight loss outcomes and the resolution of comorbid conditions in patients with similar clinical profiles. We also aim to identify whether increased use of the app is associated with increased physical activity and to understand which aspects of the software the participants find most useful and beneficial in supporting their efforts.

3. Methods and Materials

In the first 10 months of the study, 420 patients were recruited at different stages of their weight loss journey ranging from 6 months before until >2 years following bariatric surgery at the Imperial Weight Centre. Physical activity [i.e. step count, walk time (mins) and distance walked (km)] was recorded using the free, commercial ‘Moves’ app (by Protogeo, see Figure 1), with an adjunct app collecting weight, mood, and wakefulness data. The Moves app classifies and collates detailed physical activity using the smartphone’s accelerometer sensor and location data and intermittently transmits to our servers when the phone has an internet connection.

4. Results

To date, we have accurately tracked 255 participants (mean age 43 years; 74% female), for a median of 80 days each (range 1-252 days, partly depending on when they were recruited), and for 14 hours per day. Of this group of participants, 100 underwent a Roux-en-Y gastric bypass, 54 had a sleeve gastrectomy, and 15 were fitted with an adjustable gastric band - with the remaining awaiting surgery (n=86). The average BMI of patients awaiting surgery was 46.8kg/m2 (range 30.1 – 78.5kg/m2) compared to a BMI of 36.3kg/m2 for the post-surgery group, (range 20.4 - 55.7kg/m2).

Results thus far reveal that the average daily activity (mainly walking) was 16 minutes (SD=14.69) for pre-surgery participants and 21 minutes for post-surgery participants (SD=15.43): both of which are well below the recommended level of 30 minutes per day. (Comparisons of cross sectional time-points revealed that mean daily walking time did not increase significantly from pre-surgery to 2 years post-surgery, despite weight loss [F (6, 255) = 1.68, p=0.126]).

5. Conclusions

We have not yet begun to use machine learning software to analyse the rich data we are collecting, but this approach to tracking of physical activity of bariatric patients up to two years after surgery represents a significant advance on prior studies, which used accelerometers or pedometers and only monitored patients for three or four days before and after surgery [5;7]. Limitations of this work include data deficits due to excessive battery drain, disabled GPS and restrictions in working environments where phone use is prohibited thus preventing the recording of short bursts of activity throughout the

Figure 1. Screen shot from Moves app

working day. Recruitment will continue to the end of the project (April 2016) and tracking will continue into 2017.

References

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