An orientation free adaptive step detection algorithm using a smart phone in physical activity monitoring

In this paper we present an Orientation Free Adaptive Step Detection (OFASD) algorithm for deployment in a smart phone for the purposes of physical activity monitoring. The OFASD algorithm detects individual steps and measures a user’s step counts using the smart phone’s in-built accelerometer. The algorithm considers both the variance of an individual’s walking pattern and the orientation of the smart phone. Experimental validation of the algorithm involved the collection of data from 10 participants using five phones (worn at five different body positions) whilst walking on a treadmill at a controlled speed for periods of 5 min. Results indicated that, for steps detected by the OFASD algorithm, there were no significant differences between where the phones were placed on the body (p > 0.05). The mean step detection accuracies ranged from 93.4 % to 96.4 %. Compared to measurements acquired using existing dedicated commercial devices, the results demonstrated that using a smart phone for monitoring physical activity is promising, as it adds value to an accepted everyday accessory, whilst imposing minimum interaction from the user. The algorithm can be used as the underlying component within an application deployed within a smart phone designed to promote self-management of chronic disease where activity measurement is a significant factor, as it provides a practical solution, with minimal requirements for user intervention and less constraints than current solutions.

The physical activity loyalty card scheme:Development and application of a novel system for incentivizing behaviour change

In the Public Health White Paper "Healthy Lives, Healthy People" (2010), the UK Government emphasised using incentives and "nudging" to encourage positive, healthy behaviour changes. However, there is little evidence that nudging is effective, in particular for increasing physical activity. We have created a platform to research the effectiveness of health-related behaviour change interventions and incentive schemes. The system consists of an outward-facing website, incorporating tools for incentivizing behaviour change, and a novel physical activity monitoring system. The monitoring system consists of the "Physical Activity Loyalty Card", which contains a passive RFID tag, and a contactless sensor network to detect the cards. This paper describes the application of this novel web-based system to investigate the effectiveness of non-cash incentives to "nudge" adults to undertake more physical activity. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

Exploring the use of physical activity loyalty cards for behaviour change in public health: randomised controlled trial

Abstract
Background Physical inactivity is a major public health concern, and more innovative approaches are urgently needed to address it. The UK Government supports the use of incentives and so-called nudges to encourage healthy behaviour changes, and has encouraged business sector involvement in public health through the Public Health Responsibility Deal. To test the effectiveness of provision of incentives to encourage adults to increase their physical activity, we
recruited 406 adults from a workplace setting (office-based) to take part in an assessor-blind randomised controlled trial.
Methods
We developed the physical activity loyalty card scheme, which integrates a novel physical activity tracking system with web-based monitoring (palcard). Participants were recruited from two buildings at Northern Ireland’s main
government offices and were randomly allocated (grouped by building [n=2] to reduce contamination) to either incentive group (n=199) or no incentive group (n=207). We included participants aged 16–65 years, based at the worksite 4 days or more per week and for 6 h or more per day, and able to complete 15 min of moderate-paced walking (self-report). Exclusion criteria included having received specific advice by a general practitioner not to exercise. A statistician not involved in administration of the trial prepared a computer-generated random allocation sequence. Random assignments were placed in individually numbered, sealed envelopes by the statistician to ensure concealment of allocation. Only the assessor was masked to assignment. Sensors were placed along footpaths and the gym in the workplace. Participants scanned their loyalty card at the sensor when undertaking physical activity (eg, walking), which logged activity. Participants in the incentive group monitored their physical activity, collected points, and received rewards (retail vouchers) for minutes of physical activity completed over the 12-week intervention. Rewards were vouchers sponsored by local retailers. Participants in the no incentive group used their loyalty card to self-monitor their physical activity but were not able to earn points or receive rewards. The primary outcome was change in minutes of moderate to vigorous physical activity with the Global Physical Activity Questionnaire, measured at baseline, week 12, and 6 months. Activity was objectively measured with the tracking system over the 12-week intervention. Mann Whitney U tests were done to assess change between groups.
Findings
The mean age of participants was 43·32 years (SD 9·37), and 272 (67%) were women. We obtained follow-up data from 353 (87%) participants at week 12 and 341 (84%) at 6 months. At week 12, participants in the incentive group increased moderate to vigorous physical activity by a median of 60 min per week (IQR –10 to 120) compared with 30 min per week (–60 to 90) in the no incentive group (p=0·05). At 6 months, participants in the incentive group had
increased their moderate to vigorous physical activity by 30 min per week (–60 to 100) from baseline compared with 0 min per week (–115 to 1110) in the no incentive group (p=0·099). We noted no significant differences between groups
for use of loyalty card (p=0·18). Participants in the incentive group recorded a mean of 60·22 min (95% CI 50·90–69·55) of physical activity per week with their loyalty card on week 1 and 23·56 min (17·06–30·06) at week 12, which was similar to that for those in the no incentive group (59·74 min, 51·24–68·23, at week 1; 20·25 min, 14·45–26·06, at week 12; p=0·94 for differences between groups at week 1; p=0·45 for differences between groups at week 12).
Interpretation:
Financial incentives showed a short-term behaviour change in physical activity. This innovative study contributes to the necessary evidence base, and has important implications for physical activity promotion and business engagement in health. The optimum incentive-based approach needs to be established. Results should be interpreted with some caution as the analyses of secondary outcomes were not adjusted for multiple comparisons.

Steps to a better Belfast: physical activity assessment and promotion in primary care

BACKGROUND: Low physical activity (PA) levels which increase the risk of chronic disease are reported by two-thirds of the general UK population. Promotion of PA by primary healthcare professionals is advocated but more evidence is needed regarding effective ways of integrating this within everyday practice. This study aims to explore the feasibility of a randomised trial of a pedometer-based intervention, using step-count goals, recruiting patients from primary care. METHOD: Patients, aged 35-75, attending four practices in socioeconomically deprived areas, were invited to complete a General Practice PA Questionnaire during routine consultations. Health professionals invited 'inactive' individuals to a pedometer-based intervention and were randomly allocated to group 1 (prescribed a self-determined goal) or group 2 (prescribed a specific goal of 2500 steps/day above baseline). Both groups kept step-count diaries and received telephone follow-up at 1, 2, 6 and 11 weeks. Step counts were reassessed after 12 weeks. RESULTS: Of the 2154 patients attending, 192 questionnaires were completed (8.9%). Of these, 83 were classified as 'inactive'; 41(10 men; 31 women) completed baseline assessments, with the mean age of participants being 51 years. Mean baseline step counts were similar in group 1 (5685, SD 2945) and group 2 (6513, SD 3350). The mean increase in steps/day was greater in groups 1 than 2 ((2602, SD 1957) vs (748, SD 1997) p=0.005). CONCLUSIONS: A trial of a pedometer-based intervention using self-determined step counts appears feasible in primary care. Pedometers appear acceptable to women, particularly at a perimenopausal age, when it is important to engage in impact loading activities such as walking to maintain bone mineral density. An increase of 2500 steps/day is achievable for inactive patients, but the effectiveness of different approaches to realistic goal-setting warrants further study.

Urban greenways have the potential to increase physical activity levels cost-effectively

BACKGROUND: For many, physical activity has been engineered out of daily life, leading to high levels of sedentariness and obesity. Multi-faceted physical activity interventions, combining individual, community and environmental approaches, have the greatest potential to improve public health, but few have been evaluated. METHODS: Approximately 100 000 people may benefit from improved opportunities for physical activity through an urban regeneration project in Northern Ireland, the Connswater Community Greenway. Using the macro-simulation PREVENT model, we estimated its potential health impacts and cost-effectiveness. To do so, we modelled its potential impact on the burden from cardiovascular disease, namely, ischaemic heart disease, type 2 diabetes mellitus and stroke, and colon and breast cancer, by the year 2050, if feasible increases in physical activity were to be achieved. RESULTS: If 10% of those classified as 'inactive' (perform less than 150 minutes of moderate activity/week) became 'active', 886 incident cases (1.2%) and 75 deaths (0.9%) could be prevented with an incremental cost-effectiveness ratio of £4469/disability-adjusted life year. For effectiveness estimates as low as 2%, the intervention would remain cost-effective (£18 411/disability-adjusted life year). Small gains in average life expectancy and disability-adjusted life expectancy could be achieved, and the Greenway population would benefit from 46 less years lived with disability. CONCLUSION: The Greenway intervention could be cost-effective at improving physical activity levels. Although the direct health gains are predicted to be small for any individual, summed over an entire population, they are substantial. In addition, the Greenway is likely to have much wider benefits beyond health.

Chronic workplace stress and insufficient physical activity: a cohort study

Objectives To examine whether exposure to workplace stressors predicts changes in physical activity and the risk of insufficient physical activity.

Methods Prospective data from the Finnish Public Sector Study. Repeated exposure to low job control, high job demands, low effort, low rewards and compositions of these (job strain and effort-reward imbalance) were assessed at Time 1 (2000-2002) and Time 2 (2004). Insufficient physical activity (<14 metabolic equivalent task hours per week) was measured at Time 1 and Time 3 (2008). The effect of change in workplace stressors on change in physical activity was examined using fixed-effects (within-subject) logistic regression models (N=6665). In addition, logistic regression analysis was applied to examine the associations between repeated exposure to workplace stressors and insufficient physical activity (N=13 976). In these analyses, coworker assessed workplace stressor scores were used in addition to individual level scores.

Results The proportion of participants with insufficient physical activity was 24% at baseline and 26% at follow-up. 19% of the participants who were sufficiently active at baseline became insufficiently active at follow-up. In the fixed-effect analysis, an increase in workplace stress was weakly related to an increase in physical inactivity within an individual. In between-subjects analysis, employees with repeated exposure to low job control and low rewards were more likely to be insufficiently active at follow-up than those with no reports of these stressors; fully adjusted ORs ranged from 1.11 (95% CI 1.00 to 1.24) to 1.21 (95% CI 1.05 to 1.39).

Conclusions Workplace stress is associated with a slightly increased risk of physical inactivity.

A randomised control trial of experiential learning to promote physical activity

The paucity of training in physical activity (PA) promotion in UK medical schools is a barrier to health professionals' promotion of PA to their patients. Doctors who are more physically active are more likely to counsel patients in this regard. We used a randomised controlled trial (RCT) to examine the effect of an intervention which engaged students in goal-setting, using pedometer step counts, on their PA behaviour and intentions to promote PA in future practice.

Physical Activity Loyalty Cards for Behavior Change:A Quasi-Experimental Study

Background: Financial incentives have been advocated by the UK and U.S. governments to encourage adoption of healthy lifestyles. However, evidence to support the use of incentives for changing physical activity (PA) behavior is sparse.
Purpose:To investigate the effectiveness of?nancial incentives to increase PA in adults in the workplace.
Design: Two-arm quasi-experimental design.
Setting/participants: Employees (n¼406) in a workplace setting in Belfast, Northern Ireland, UK.
Intervention: Using a loyalty card to collect points and earn rewards, participants (n¼199) in the Incentive Group monitored their PA levels and received ?nancial incentives (retail vouchers) for minutes of PA completed over the course of a 12-week intervention period. Participants (n¼207) in the comparison group used their loyalty card to self-monitor their PA levels but were not able to earn points or obtain incentives (No Incentive Group).
Main outcome measures:The primary outcome was minutes of PA objectively measured using a novel PA tracking system at baseline (April 2011); Week 6 (June 2011); and Week 12 (July 2011).
Other outcomes, including a self-report measure of PA, were collected at baseline, Week 12, and 6 months (October 2011). Data were analyzed in June 2012.
Results: No signi?cant differences between groups were found for primary or secondary outcomes at the 12-week and 6-month assessments. Participants in the Incentive Group recorded 17.52 minutes of PA/week (95% CI¼12.49, 22.56) compared to 16.63 minutes/week (95% CI¼11.76, 21.51) in the No Incentive Group at Week 12 (p¼0.59). At 6 months, participants in the Incentive Group recorded 26.18 minutes of PA/week (95% CI¼20.06, 32.29) compared to 24.00 minutes/week (95% CI¼17.45, 30.54) in the No Incentive Group (p¼0.45).
Conclusions: Financial incentives did not encourage participants to undertake more PA than selfmonitoring PA. This study contributes to the evidence base and has important implications for increasing participation in physical activity and fostering links with the business sector. (Am J Prev Med 2013;45(1):56–63) © 2013 American Journal of Preventive Medicine

Physical activity and the rejuvenation of Connswater (PARC study): protocol for a natural experiment investigating the impact of urban regeneration on public health

Background: There is a dearth of evidence regarding the impact of urban regeneration projects on public health, particularly the nature and degree to which urban regeneration impacts upon health-related behaviour change. Natural experiment methodology enables comprehensive large-scale evaluations of such interventions. The Connswater Community Greenway in Belfast is a major urban regeneration project involving the development of a 9 km linear park, including the provision of new cycle paths and walkways. In addition to the environmental improvements, this complex intervention involves a number of programmes to promote physical activity in the regenerated area. The project affords a unique opportunity to investigate the public health impact of urban regeneration.

Methods/Design: The evaluation framework was informed by the socio-ecological model and guided by the RE-AIM Framework. Key components include: (1) a quasi-experimental before-and-after survey of the Greenway population (repeated cross-sectional design), in tandem with data from a parallel Northern Ireland-wide survey for comparison; (2) an assessment of changes in the local built environment and of walkability using geographic information systems; (3) semi-structured interviews with a purposive sample of survey respondents, and a range of community stakeholders, before and after the regeneration project; and (4) a cost-effectiveness analysis. The primary outcome is change in proportion of individuals identified as being regularly physically active, according to the current UK recommendations. The RE-AIM Framework will be used to make an overall assessment of the impact of the Greenway on the physical activity behaviour of local residents.

Discussion: The Connswater Community Greenway provides a significant opportunity to achieve long-term, population level behaviour change. We argue that urban regeneration may be conceptualised meaningfully as a complex intervention comprising multiple components with the potential, individually and interactively, to affect the behaviour of a diverse population. The development and implementation of our comprehensive evaluation framework reflects this complexity and illuminates an approach to the empirical, rigorous evaluation of urban regeneration. More specifically, this study will add to the much needed evidence-base about the impact of urban regeneration on public health as well as having important implications for the development of natural experiment methodology.

A lesson in business: cost-effectiveness analysis of a novel financial incentive intervention for increasing physical activity in the workplace

Background: Recently both the UK and US governments have advocated the use of financial incentives to encourage healthier lifestyle choices but evidence for the cost-effectiveness of such interventions is lacking. Our aim was to perform a cost-effectiveness analysis (CEA) of a quasi-experimental trial, exploring the use of financial incentives to increase employee physical activity levels, from a healthcare and employer’s perspective.

Methods: Employees used a ‘loyalty card’ to objectively monitor their physical activity at work over 12 weeks. The Incentive Group (n=199) collected points and received rewards for minutes of physical activity completed. The No Incentive Group (n=207) self-monitored their physical activity only. Quality of life (QOL) and absenteeism were assessed at baseline and 6 months follow-up. QOL scores were also converted into productivity estimates using a validated algorithm. The additional costs of the Incentive Group were divided by the additional quality adjusted life years (QALYs) or productivity gained to calculate incremental cost effectiveness ratios (ICERs). Cost-effectiveness acceptability curves (CEACs) and population expected value of perfect information (EVPI) was used to characterize and value the uncertainty in our estimates.

Results: The Incentive Group performed more physical activity over 12 weeks and by 6 months had achieved greater gains in QOL and productivity, although these mean differences were not statistically significant. The ICERs were £2,900/QALY and £2,700 per percentage increase in overall employee productivity. Whilst the confidence intervals surrounding these ICERs were wide, CEACs showed a high chance of the intervention being cost-effective at low willingness-to-pay (WTP) thresholds.

Conclusions: The Physical Activity Loyalty card (PAL) scheme is potentially cost-effective from both a healthcare and employer’s perspective but further research is warranted to reduce uncertainty in our results. It is based on a sustainable “business model” which should become more cost-effective as it is delivered to more participants and can be adapted to suit other health behaviors and settings. This comes at a time when both UK and US governments are encouraging business involvement in tackling public health challenges.

Using Pedometer Step-Count Goals to Promote Physical Activity in Cardiac Rehabilitation: A Feasibility Study of a Controlled Trial

Background: There is a need to improve the effectiveness of strategies to help cardiac rehabilitation patients achieve recommended levels of physical activity; the use of pedometers requires further research. We aimed to examine the feasibility of a randomised controlled trial, of an intervention using pedometer step-count goals, to promote physical activity for cardiac rehabilitation patients. Methods: We invited patients who completed a supervised cardiac rehabilitation programme to participate in this community-based study. Consenting participants wore a Yamax CW-701 pedometer for one week, blinded to stepcount readings, before being randomly allocated to groups. Intervention groups were told their step-counts; working with a clinical facilitator (nurse or physiotherapist) individually, they set daily step-count goals and reviewed these weekly. Baseline step-counts were hidden from controls, who were not given pedometers but received ongoing weekly facilitator support. After six weeks both groups wore ‘blinded’ pedometers for outcome assessment and participated in semi-structured interviews which explored their experiences of the study. Outcomes included rates of uptake, adherence and completion of measures, including step-counts, quality of life (EQ-5D) and stage of behaviour change. Results: Four programme groups were recruited; two received the intervention. Of 68 invitees, 45 participated (66%) (19 intervention; 26 control). Forty-two (93%) completed the outcomes. Baseline characteristics were comparable between groups. Mean steps/day increased more for intervention participants (2,742; 95%CI 1,169 to 4,315) than controls (-42; 95%CI -1,102 to 1,017) (p=0.004). The intervention and on-going clinical contact were welcomed; participants considered that step-counts, compared to time-related targets, encouraged them to become more active. Conclusion: These findings suggest that an intervention using individually tailored step-count goals may help increase and sustain physical activity following a cardiac rehabilitation programme. A definitive randomised controlled trial using blinded outcome measurements is feasible and of potential value in determining how best to translate physical activity advice into practice.