A Low-Cost Calibration Method for Low-Cost MEMS Accelerometers Based on 3D Printing.

A ubiquitous sensor in embedded systems is the accelerometer, as it enables a range of applications. However, accelerometers experience nonlinearities in their outputs caused by error terms and axes misalignment. These errors are a major concern because, in applications such as navigations systems, they accumulate over time, degrading the position accuracy. Through a calibration procedure, the errors can be modeled and compensated. Many methods have been proposed; however, they require sophisticated equipment available only in laboratories, which makes them complex and expensive. In this article, a simple, practical, and low-cost calibration method is proposed. It uses a 3D printed polyhedron, benefiting from the popularisation and low-cost of 3D printing in the present day. Additionally, each polyhedron could hold as much as 14 sensors, which can be calibrated simultaneously. The method was performed with a low-cost sensor and it significantly reduced the root-mean-square error (RMSE) of the sensor output. The RMSE was compared with the reported in similar proposals, and our method resulted in higher performance. The proposal enables accelerometer calibration at low-cost, and anywhere and anytime, not only by experts in laboratories. Compensating the sensor's inherent errors thus increases the accuracy of its output.

Deriving objectively-measured sedentary indices from free-living accelerometry data in rural and urban African settings: a cost effective approach.

OBJECTIVES: To investigate the agreement between two data reduction approaches for detecting sedentary breaks from uni-axial accelerometry data collected in human participants. Free-living, uni-axial accelerometer data (n = 318) were examined for sedentary breaks using two different methods (Healy-Matthews; MAH/UFFE). The data were cleaned and reduced using MAH/UFFE Analyzer software and custom Microsoft Excel macro's, such that the average daily sedentary break number were calculated for each data record, for both methods. RESULTS: The Healy-Matthews and MAH/UFFE average daily break number correlated closely (R2 = 99.9%) and there was high agreement (mean difference: + 0.7 breaks/day; 95% limits of agreement: - 0.06 to + 1.4 breaks/day). A slight bias of approximately + 1 break/day for the MAH/UFFE Analyzer was evident for both the regression and agreement analyses. At a group level there were no statistically or practically significant differences within sample groups between the two methods.

A preliminary trial examining a 'real world' approach for increasing physical activity among breast cancer survivors: findings from project MOVE.

BACKGROUND: Physical activity (PA) is a safe and effective strategy to help mitigate health challenges associated with breast cancer (BC) survivorship. However, the majority of BC survivors are not meeting the minimum recommended PA (≥150 min of moderate to vigorous intensity). Project MOVE was developed as a model for increasing PA that combined a) Microgrants: funds ($2000) awarded to applicant groups to develop and implement a PA initiative and b) Financial incentives: a reward ($500) for increasing group PA. The purpose of this paper was to provide an exploratory analysis of effectiveness of Project MOVE on PA behavior, PA motivation, and quality of life (QoL) in female BC survivors. The differential outcomes between women meeting and not meeting PA guidelines were also investigated. METHODS: This pre-post test, preliminary trial included groups of adult (18+ years) self-identified female BC survivors, who were post-surgery and primary systemic chemo- and radiation therapy, and living in British Columbia, Canada. PA was assessed by accelerometry. PA motivation and QoL were assessed by self-report. Data were collected at baseline, 6-months, and 12-month time points. Repeated measures mixed ANOVAs were used to test changes in the main outcomes. RESULTS: A total of 10 groups were awarded microgrants between May 2015 and January 2016. Groups comprised of 8 to 12 women with a total of 87 participants. A statistically significant increase was found between time points on weekly moderate to vigorous PA (p = .012). This was mediated by a significant interaction between those meeting PA guidelines and those not meeting guidelines at baseline by time points (p = .004), with those not meeting guidelines at baseline showing the greatest increase in MVPA. A statistically significant difference across time points was found for intrinsic motivation (p = .02), physical functioning (p < .001), physical health limitations (p = .001), emotional health limitations (p = .023), social functioning (p = .001) and general health (p = .004). CONCLUSION: These results provide promising support for a unique approach to increasing PA among BC survivors by empowering women and optimizing PA experiences through the use of microgrants and financial incentives. TRIAL REGISTRATION: ClinicalTrials.gov NCT03548636 , Retrospectively registered June 7, 2018.

The validity of the commercially-available, low-cost, wrist-worn Movband accelerometer during treadmill exercise and free-living physical activity.

Low-cost physical activity monitors may provide a more accurate measure of physical activity than subjective methods (e.g., self-report) while being less costly than research-grade accelerometers. The present study assessed the validity of a low-cost monitor (Movband 2) to estimate physical activity behavior/intensity. Participants (N = 23, n = 16 female, BMI = 22.9 ± 4.0 kg/m2, age = 21.9 ± 1.6 years) completed four, five-minute treadmill stages (2.0, 3.0, 4.0, 5.0 MPH) while wearing both the Movband and the previously-validated Actigraph monitor. Oxygen consumption (VO2) was recorded during each stage (Laboratory assessment). A subset (n = 15, n = 10 female, BMI = 22.2 ± 3.2 kg/m2, age = 21.5 ± 0.8 years) of these participants then wore the two accelerometers for three days (Free-living assessment). During the Laboratory assessment there were strong, significant (r = 0.94, p ≤ 0.001) relationships between Movband and Actigraph counts and VO2. During Free-living assessment there was also a strong, significant (r = 0.97, p < 0.001) correlation between Movband and Actigraph counts. The low-cost, Movband accelerometer appears to provide a valid assessment of physical activity behavior/intensity.

Assessing a low-cost accelerometer-based technique to estimate spatial gait parameters of lower-limb prosthesis users.

BACKGROUND AND AIM: Inexpensive methods for characterizing lower-limb prosthetic gait allow clinicians to monitor gait quality. This study assessed an established method for estimating step length using a low-cost accelerometer to estimate distance walked in lower-limb prosthesis users and explore the use of subject-specific correction factors. TECHNIQUE: A three-axis accelerometer was attached to participants using straps. Validity and test-retest reliability of step length was assessed in able-bodied individuals using a motion capture system. Validity of distance walked was assessed with lower-limb prosthesis users. A regression equation was developed for prosthesis users to estimate a correction factor that minimized error. DISCUSSION: The system demonstrated excellent reliability and minimal mean error for both participant groups, but subject-specific correction factors did not provide substantial benefit. Estimate variability was high, suggesting the need for further refinement. Estimating distance walked and step length from low-cost accelerometers may be a valid, clinically accessible method for characterizing prosthetic gait. CLINICAL RELEVANCE: The use of a low-cost accelerometer may provide valid means for estimating step length and distance walked of lower-limb prosthesis users in a clinical environment for monitoring patient outcomes.

Comparison of a Commercial Accelerometer with Polysomnography and Actigraphy in Children and Adolescents.

STUDY OBJECTIVES: To evaluate the reliability and validity of the commercially available Fitbit Ultra (2012) accelerometer compared to polysomnography (PSG) and two different actigraphs in a pediatric sample. DESIGN AND SETTING: All subjects wore the Fitbit Ultra while undergoing overnight clinical polysomnography in a sleep laboratory; a randomly selected subset of participants also wore either the Ambulatory Monitoring Inc. Motionlogger Sleep Watch (AMI) or Phillips-Respironics Mini-Mitter Spectrum (PRMM). PARTICIPANTS: 63 youth (32 females, 31 males), ages 3-17 years (mean 9.7 years, SD 4.6 years). MEASUREMENTS: Both "Normal" and "Sensitive" sleep-recording Fitbit Ultra modes were examined. Outcome variables included total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE). Primary analyses examined the differences between Fitbit Ultra and PSG using repeated-measures ANCOVA, with epoch-by-epoch comparisons between Fitbit Ultra and PSG used to determine sensitivity, specificity, and accuracy. Intra-device reliability, differences between Fitbit Ultra and actigraphy, and differences by both developmental age group and sleep disordered breathing (SDB) status were also examined. RESULTS: Compared to PSG, the Normal Fitbit Ultra mode demonstrated good sensitivity (0.86) and accuracy (0.84), but poor specificity (0.52); conversely, the Sensitive Fitbit Ultra mode demonstrated adequate specificity (0.79), but inadequate sensitivity (0.70) and accuracy (0.71). Compared to PSG, the Fitbit Ultra significantly overestimated TST (41 min) and SE (8%) in Normal mode, and underestimated TST (105 min) and SE (21%) in Sensitive mode. Similar differences were found between Fitbit Ultra (both modes) and both brands of actigraphs. CONCLUSIONS: Despite its low cost and ease of use for consumers, neither sleep-recording mode of the Fitbit Ultra accelerometer provided clinically comparable results to PSG. Further, pediatric sleep researchers and clinicians should be cautious about substituting these devices for validated actigraphs, with a significant risk of either overestimating or underestimating outcome data including total sleep time and sleep efficiency.

Instrumenting gait with an accelerometer: a system and algorithm examination.

Gait is an important clinical assessment tool since changes in gait may reflect changes in general health. Measurement of gait is a complex process which has been restricted to the laboratory until relatively recently. The application of an inexpensive body worn sensor with appropriate gait algorithms (BWM) is an attractive alternative and offers the potential to assess gait in any setting. In this study we investigated the use of a low-cost BWM, compared to laboratory reference using a robust testing protocol in both younger and older adults. We observed that the BWM is a valid tool for estimating total step count and mean spatio-temporal gait characteristics however agreement for variability and asymmetry results was poor. We conducted a detailed investigation to explain the poor agreement between systems and determined it was due to inherent differences between the systems rather than inability of the sensor to measure the gait characteristics. The results highlight caution in the choice of reference system for validation studies. The BWM used in this study has the potential to gather longitudinal (real-world) spatio-temporal gait data that could be readily used in large lifestyle-based intervention studies, but further refinement of the algorithm(s) is required.

Lessons learned from a collaborative field-based collection of physical activity data using accelerometers.

CONTEXT: Recent improvements in the accuracy and availability of accelerometers present an opportunity to increase the validity of physical activity assessment. While use of these devices is now pervasive among researchers, accelerometers have not been widely used by community-based public health practitioners. OBJECTIVE: To present a case example of field-based data collection using accelerometers with youth. METHOD: A collaborative research team, including state- and county-level public health practitioners and university researchers, collected accelerometer data from 1313 youth, aged 9 to 14 years, in 20 North Carolina counties. RESULTS: This case example highlights some considerations for how to improve communication and streamline data collection logistics within a multidisciplinary research team. It demonstrates that a collaborative model can make objective physical activity evaluation feasible in community settings with limited resources. CONCLUSIONS: Lessons learned by our research team about coordinating the logistics of accelerometer use and scheduling a large-scale data collection in multiple sites can be adapted by other researchers and community-based practitioners who aim to evaluate physical activity using accelerometers or other mobile data collection devices.