Accelerometers in Our Pocket: Does Smartphone Accelerometer Technology Provide Accurate Data?

Abstract

This study evaluates accelerometer performance of three new state of the art smartphones and focuses on accuracy. The motivating research question was whether accelerator accuracy obtained with these off-the-shelf modern smartphone accelerometers was or was not statistically different from that of a gold-standard reference system. We predicted that the accuracy of the three modern smartphone accelerometers in human movement data acquisition do not differ from that of the Vicon MX motion capture system. To test this prediction, we investigated the comparative performance of three different commercially available current generation smartphone accelerometers among themselves and to a gold-standard Vicon MX motion capture system. A single subject design was implemented for this study. Pearson’s correlation coefficients® were calculated to verify the validity of the smartphones’ accelerometer data against that of the Vicon MX motion capture system. The Intraclass Correlation Coefficient (ICC) was used to assess the smartphones’ accelerometer performance reliability compared to that of the Vicon MX motion capture system. Results demonstrated that (a) the tested smartphone accelerometers are valid and reliable devices for estimating accelerations and (b) there were not significant differences among the three current generation smartphones and the Vicon MX motion capture system’s mean acceleration data. This evidence indicates how well recent generation smartphone accelerometer sensors are capable of measuring human body motion. This study, which bridges a significant information gap between the accuracy of accelerometers measured close to production and their accuracy in actual smartphone research, should be interpreted within the confines of its scope, limitations and strengths. Further research is warranted to validate our arguments, suggestions, and results, since this is the first study on this topic.

Smartphone Technology to Remotely Measure Postural Sway during Double- and Single-Leg Squats in Adults with Femoroacetabular Impingement and Those with No Hip Pain

“…First, participants used a range of personal smartphone devices, and this may introduce potential errors due to data sampling from variations in smartphone devices, operating software platforms, and motion sensors. Grouios et al [36] compared acceleration data from three smartphones, including iPhone 12 Pro Max, Samsung Galaxy S21 Ultra, and Huawei P Smart, and concluded that the mean acceleration data were not statistically different between the devices. This result was similar to other research studies [37,38] that compared accelerometer sensor performance between commercially available smartphones, suggesting that modern smartphone accelerometers can be used for measuring human movement and be employed in clinical research.…”

Validation of gait analysis using smartphones: Reliability and validity

“…HD: This study focused on demonstrating the feasibility of gait analysis using smartphones and was thus completed in a relatively small cohort of healthy young adults. 10 – 14 We chose young, healthy adults as the experimental cohort based on their ease of cooperation and ability to perform standardized gait tests in experimental settings with complex equipment configurations; they can provide controllable and reliable gait patterns at different walking speeds. This study recruited 30 young, healthy adults (16 males and 14 females; age 26.400 ± 1.545 years; height 172.333 ± 8.314 cm; weight 65.370 ± 11.357 kg).…”

“…As shown in Figure 2 , two smartphones (iPhone 13) were attached to the waist and thigh, while an inertial measurement unit (N200, WHEELTEC, China; sampling rate: 100 Hz) was fixed at the shank as the reference device for validation purposes. Each participant was asked to walk six gait cycles at self-selected 10 , 12 – 14 , 17 low, normal, and high speeds along a flat corridor. Normal speed walking is defined as walking at a comfortable speed, high-speed walking is preferred, and as fast as possible, and low-speed walking is defined as walking cautiously.…”

“…Studies have shown that smartphones can effectively measure and quantify human body motion. 10 Furthermore, multiple studies demonstrate the practical application of built-in smartphone sensors such as accelerometers and gyroscopes in gait analysis, covering a range of populations, including healthy adults, 11 – 14 elderly individuals, 15 individuals with multiple sclerosis, 16 and Parkinson's disease patients. 17 Significant progress has been made in gait analysis with smartphones.…”

Human Activity Recognition Algorithm with Physiological and Inertial Signals Fusion: Photoplethysmography, Electrodermal Activity, and Accelerometry

“…[10]. The prevalent use of accelerometers in HAR may be explained by the low cost and small size of the device as standalone sensors, and additionally, their low energy consumption and high feature performance, as demonstrated in modern smartphones, further contribute to their widespread adoption [11,12].…”