Sensor Validation Research Articles

Trace vapor generator for Explosives and Narcotics (TV-Gen).

The Trace Vapor Generator for Explosives and Narcotics (TV-Gen) is a portable and compact instrument designed to deliver a continuous source of trace-level vapors and vapor mixtures. It provides a tool to assist in the independent validation and verification of new materials and sensors under development for the vapor detection of explosives and narcotics. The design was conceived for use with a broad range of analytes, detection systems, materials, and sensors and to switch easily between the clean and analyte vapor streams. The TV-Gen system utilizes nebulization of aqueous analyte solutions, an oven to promote efficient transport, and a control box that provides dedicated computer control with logging capabilities. Resultant vapor streams are stable over several hours, with the vapor concentration controlled by a combination of aqueous analyte solution concentration, liquid flow rate through the nebulizer, and volume flow rate of air through the TV-Gen manifold.

Validation Of Player Tracking Sensors For Measuring Sprint Speed With Collegiate Ice Hockey Players

Validation Of Player Tracking Sensors For Measuring Sprint Speed With Collegiate Ice Hockey Players

Validation of gyroscope sensors for snow sports performance monitoring

Abstract Wearable sensors that can be used to measure human performance outcomes are becoming increasingly popular within sport science research. Validation of these sensors is vital to ensure accuracy of extracted data. The aim of this study was to establish the validity and reliability of gyroscope sensors contained within three different inertial measurement units (IMU). Three IMUs (OptimEye, I Measure U and Logger A) were fixed to a mechanical calibration device that rotates through known angular velocities and positions. RMS scores for angular displacement, which were calculated from the integrated angular velocity vectors, were 3.85° ± 2.21° and 4.34° ± 2.57° for the OptimEye and IMesU devices, respectively. The RMS error score for the Logger A was 22.76° ± 23.22°, which was attributed to a large baseline shift of the angular velocity vector. After a baseline correction of all three devices, RMS error scores were all below 3.90°. Test re-test reliability of the three gyroscope sensors were high with coefficient of variation (CV%) scores below 2.5%. Overall, the three tested IMUs are suitable for measuring angular displacement of snow sports manoeuvres after baseline corrections have been made. Future studies should investigate the accuracy and reliability of accelerometer and magnetometer sensors contained in each of the IMUs to be used to identify take-off and landing events and the orientation of the athlete at those events.

A dataset for wearable sensors validation in gait analysis.

The article describes a dataset of gait measures acquired to validate the use of wearable sensors in gait analysis since its measurements can be compared with those provided by the stereophotogrammetric system. The comparison with a gold standard in gait analysis makes the dataset useful for the development, testing and validation of algorithms for estimating gait parameters.The dataset contains measurements simultaneously acquired by the wearable sensors and the stereophotogrammetric system during an acquisition campaign performed on 5 healthy subjects (2 females and 3 males aged between 25 and 35 years). In the acquisition campaign the involved subjects carried out a motion task wearing the wearable sensors and reflective markers of the stereophotogrammetric system. In particular, the subjects wore in each foot a wearable sensor on the instep and a reflective marker on heel, first metatarsal head, fifth metatarsal head, and above the sensor, respectively. During the motion task each subject walked over an 11-meter long walkway according to its own course. The 5 subjects involved in the acquisition campaign performed 3 repetitions of the motion task, for a total of 15 trials in where the measures collected by wearable sensors and the stereophotogrammetric system can be compared.

Development of a Low-cost Ultrasonic Sensor for Groundwater Monitoring in Coastal Environments: Validation using Field and Laboratory Observations

Gonzaga, B.A.; Alves, D.C.L.; Albuquerque, M.G.; Espinoza, J.M.A.; Almeida, L.P.M., and Weschenfelder, J., 2020. Development of a low-cost ultrasonic sensor for groundwater monitoring in coastal environments: Validation using field and laboratory observations. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1001–1005. Coconut Creek (Florida), ISSN 0749-0208.This study presents the development and validation of a low-cost ultrasonic sensor (HCSR 04), coupled to an open source Arduino microcontroller platform, for groundwater monitoring in coastal environments. Given the fact that low-lying coastal zones are regions naturally prone to flooding (due to oceanic forcing and pluviosity) and densely occupied, monitoring groundwater variations is crucial for the management of flood-related events. A groundwater monitoring well was built, (made of a PVC pipe with 100 mm in diameter and 2 m long) and installed on the ground of a dune field, located in Cassino beach, southern of Brazil. The system was deployed for 84 consecutive days and programmed to perform water level measurements every 10 min. In laboratory, three units with the same hardware setup of the unit installed in the field (ultrasonic sensor coupled to the Arduino microcontroller) were installed on a 20 liter graduated PVC tube. Varying water levels were tested in the laboratory along the time (changing 1 cm every 2 minutes during 4 hours) in order to reproduce the synthetic signal. Eighty measurements were obtained for each sensor, a total of 240 for each validation process. For the laboratory validation, the results for nonparametric statistical tests (Kruskal and Wallis, and Dunn) presented a correlation of 99%, with Root mean square error (RMSE) 0.4113 and bias 0.0418. For the field tests, 3262 data collected by an ultrasonic sensor during 240 hours showed a means registration of 0.543 m. The minimum and maximum cataloged is 0.40 and 0.70 m, respectively, with 0.1076 m of standard deviation. Groundwater classical measurements, using a measuring tape, showed a mean and standard deviation of 0.544 and 0.1069 m, respectively. These preliminary tests showed that the developed monitoring system performs observations with an accuracy and precision within standard methods, therefore can be applied to monitoring changes in the level of groundwater.

Fabrication of sensitive D-fructose sensor based on facile ternary mixed ZnO/CdO/SnO2 nanocomposites by electrochemical approach

Abstracts In this approach, the nanocomposites (NCs) of ZnO/CdO/SnO2 were prepared by facile wet-chemical (co-precipitation) method in alkaline phase at low temperature. The synthesized ternary doped NCs were totally characterized in details by using various conventional methods, such as X-ray photoelectron spectroscopy (XPS), Field Emission Scanning Electron Microscopes (FESEM), Energy-dispersive X-ray spectroscopy (EDS) and powder X-ray diffraction (XRD). For the sensor application purpose, a glassy carbon electrode (GCE) was fabricated with ethanolic slurry of NCs by applying nafion adhesive (5% nafion suspension in ethanol) to result the D -fructose sensor by using electrochemical method at room conditions. A linear relation as current versus concentration of D -fructose was plotted to establish the calibration of D -fructose sensor, which is known as calibration curve. Remaking the linear segment on calibration curve, the linear dynamic range (0.1nM~0.01 mM) of D -fructose sensor was denoted. From the slope of the calibration curve and surface area of GCE (0.0316 cm2), the sensor sensitivity (28.4652 µA µM−1 cm−2) was calculated. Signal-noise ratio at 3 is used to calculated the lower limit (95.89 ± 4.79 pM) of D -fructose sensor. The analytical parameters such as response time, reproducibility, stability, validity, and repeatability of sensor were measured. Finally, the sensor was validated with real samples and found accepted and satisfactory results. Thus, the proposed method is inexpensive and simplest way to the development of reliable electrochemical sensor to detect chemicals and biochemicals in the field of food industry as well as health care sectors.

Validation of a ground-based telescope-assisted hyperspectral remote sensor for soil measurements

The utility of the ground-based soil observation laser absorption spectrometer (SOLAS) was demonstrated through spectral reflectance measurements of five soil types during laboratory- and field-based collection. The SOLAS telescope-assisted measurements were compared with proximal measurements. The spectra that were acquired at an intermediate range of 40 meters compared well with the spectra that were acquired proximally. Specimen type, range-dependent spatial resolution, and environmental conditions are discussed. The signal-to-noise ratio (SNR) was assessed and is presented as a function of wavelength for the spectral range of the receiver for each measurement condition. The proximal measurements performed outdoors under solar illumination had the greatest SNR, while the remote measurements performed indoors under artificial illumination had the lowest SNR. For the outdoor measurements, loss of signal was observed around the 1400- and 1900-nm bands due to long-path atmospheric water vapor absorption. The discussed future improvements to the SOLAS remote sensor will enable measurements of reflectance over longer ranges. Envisioned applications include remote characterization of surface materials for large construction projects (e.g., surface mines and tailings) for geohazard investigations, or for ground truthing of current and future multispectral and hyperspectral satellite data.

Low-cost solar PV soiling sensor validation and size resolved soiling impacts: A comprehensive field study in Western India

Deposition of particulate matter (PM) onto solar photovoltaic (PV) panels - known as soiling - has been estimated to reduce energy production by 10–40% in many regions of the world. Despite this, many key properties including soiling rates, PM source contributions, physical and optical properties of the deposited particles, and the impact of rain and relative humidity (RH) are not well understood. With this in mind we conducted a field study in Gandhinagar, India. Our approach combines soiling monitoring with a reference station and a low-cost digital microscopy system, sample collection for mass loading information, glass sample slides for size resolved soiling impacts, and monitoring of rain, RH, and panel temperature for insight into meteorological impacts on cleaning and soiling rates. Results indicate soiling reduces PV energy production by 0.37 ± 0.09% day−1. The low cost (<100$) digital microscope estimated soiling within ~1% of measured losses, confirming the feasibility of this low-cost alternative to expensive soiling stations. Deposited PM decreased energy production by 5.12 ± 0.55% per PM mass loading (g m−2). Microscopy analyses of field samples revealed that > 90% of deposited mass loading is from particles > 5 µm in diameter, with > 50% of the soiling impacts estimated to be from particles < 5 µm. While heavy rain cleaned PV panels, light rains and high RH contributed to a 2x soiling rate and 5-10x PM deposition velocities as compared to dry periods.

The validity of the kinect sensor for the measurement of sagittal spine curvature against the gold standard lateral spinal radiograph

The validity of the kinect sensor for the measurement of sagittal spine curvature against the gold standard lateral spinal radiograph

Chemical and Biological Sensor Capsules for Real-Time Measurement of Cell Properties in Bioreactors

Introduction Real-time bioprocess monitoring and control is needed for the scalable production and deployment of cancer cell therapies at reasonable cost. For example, CAR-T cell therapy shows promise as an effective treatment for cancer with high (70-90%) remission rates.1 However, the cost of these treatments is too expensive for their mass adoption.2 One reason for the steep price is the difficulty scaling production while ensuring delivery of an efficacious therapy to the patient. One factor preventing scalability is the lack of effective process analytical technologies. As a potential solution to this issue, we have developed a fully integrated, wireless, 3D-printed sensor capsule to be used for multiplexed sensing of critical quality attributes (CQAs), namely pH, glucose, lactate, and IL-2 concentrations within cell bioreactors. CQAs are used not only as metrics for cell viability, but also as determinants of a cell’s ability to deliver efficacious treatment. Unlike current process monitoring technology, capsule sensors are buoyant and can be propelled using impellers within the bioreactor. This allows for measurements uniformly inside the bioreactor. To our knowledge, this is the first time that 3D-printed, wireless sensor capsules have been developed for use in cell bioreactors for cancer cell therapy. Methods The capsule consists of electrochemical sensors as well as data acquisition and wireless transmission electronics integrated into a capsule made of a biocompatible polymer (Figure 1). The sensors for glucose, lactate, pH, and IL-2 along with Ag on-chip pseudo-reference electrode (pseudo-RE) were fabricated using standard lithographic techniques on silicon substrates. The reference electrode consisted of a thin-film of Ag that was later coated with polyvinyl butyral (PVB) to improve stability.3 IL-2 and pH sensing was achieved using gold electrodes. A pH-sensitive Al2O3 or HfO2 layer is deposited through atomic layer deposition on the pH sensor to achieve pH-sensitivity. Glucose and lactate sensing was achieved amperometrically using enzymes, glucose or lactase oxidase respectively, immobilized on a Pt electrode biased to 0.7 V. Detection could also be achieved potentiometrically by using the pH sensor to detect changes in pH caused by conversion of the enzyme product, H2O2, to H+.Figure 1 shows the capsule and sensor design. The capsule was 3D printed using a Stratasys Connex-350 and was designed to be fully insulated from solution except for an opening on the top revealing the sensors. The sensor chip is installed within the cap of the capsule which can be screwed off, but with wired connection to the electronics housed in the body of the capsule. This allows for simple replacement of the sensor chip while retaining the capsule components for reuse. Results and Conclusions Before testing within the capsule, the sensors were tested using microfluidics. Figure 2 shows the performance of the Ag/PVB pseudo-RE. The pseudo-RE shows a stable potential in different pH buffer solutions and similar sensitivity results when compared to a commercial reference electrode for pH sensing. By having a stable microfabricated pseudoRE, the sensing components will not limit miniaturization of the capsule. Figure 3 shows the response of the pH, lactate, and glucose sensors at different concentrations. The pH sensor shows high sensitivity (~53 mV/pH) over the range of pH 3 to 7. Glucose and lactate sensing was tested in 1X PBS. The glucose sensor shows a linear response to glucose concentrations from 1-6 mM with saturation at ~8 mM validating the use of the sensor within cell culture media.4 The lactate sensor shows sensitivity in the concentration range of 1-5 mM with saturation occurring around ~6 mM. The division of T cells requires aerobic glycolysis where glucose is converted to lactate. However, not all glucose is expected to be converted. The lactate concentration expected to be produced is ~1 mM.5 Selectivity towards IL-2 is achieved using anti-IL2 antibodies. Figure 4a shows the functionalization scheme for detection of IL-2. A thiol self-assembled monolayer (SAM) is attached to the gold electrode and then modified for amine conjugation using NHS/EDC. Anti-IL2 can then bind to the SAM and unbound sites are blocked with ethanolamine. Figure 4b reveals antibody attachment occurs optimally at pH 5. Surface plasmon resonance shows successful attachment of 10 ug/mL of IL-2 to the functionalized gold sensor. The next step is to demonstrate IL-2 sensing potentiometrically. The capsule’s wireless sensing capability was validated using pH sensing in a beaker. The pH sensing results in Figure 5b were obtained wirelessly from the capsule and were nearly identical to the results measured using our microfluidic system and Keithley-4200 lab instrument (Fig. 5a). This work has successfully demonstrated wireless sensing using a 3D-printed sensor capsule and functionality of electrochemical sensors for multiple CQAs for cell growth in bioreactors. These sensor capsules can enable scalability of the cell manufacturing process while ensuring delivery of an efficacious treatment. Future work will focus on capsule sensor validation in cell growth media and monitoring of cell growth in bioreactors.

Novel Planar Capacitive Interdigital Multifinger (IDCM) Sensor for the Detection of the Ageing of Electrical Transformer Oil

This work shows a planar interdigital sensor for rapid measurement of oils. The kit is characterised by the impedance meter, a Raspberry Pi3 and a sample port where the planar capacitive interdigital multifinger (IDCM) sensor is stored. For validation of this IDCM sensor, the data was compared with measurements performed by impedance spectroscopy (IS). The measurements show that the measured values of the new and used oils are very close, validating the IDCM sensor for fast oil measurements of oils in transformers and other devices.

Development and validation of an advanced electrochemical sensor for the fast and cheap determination of hydrochlorothiazide in urine samples using the Monte-Carlo method for uncertainty evaluation

This work describes the development, optimization, and validation of an electrochemical method for the determination of hydrochlorothiazide (HCTZ) in urine. The method allows fast, cheap and reliable determinations of recent administrations of this diuretic that can be used in doping control in sport. The response of the sensor was determined by differential pulse voltammetry (DPV). The glassy carbon electrode was modified with multiwall carbon nanotubes (MWCNT) and gold nanoparticles. The sensor is calibrated in the analysed sample matrix by the cumulative standard addition method. The method validation was based on the bottom-up evaluation of the measurement uncertainty were components were combined using the Monte Carlo Method (MCM) applicable with no restrictions regarding components uncertainty value and measurement function linearity. The developed metrological models were implemented in MS-Excel spreadsheets. The adequacy of the electrochemical measurements was assessed by comparing their relative standard uncertainty with a target value of 20% and by evaluating the compatibility of measurements with determinations performed by a reference procedure. The tools developed for the construction and optimization of working electrodes are applicable to measurements of other analytes and matrices. The used cumulative standard addition method and respective measurement uncertainty models are applicable to any kind of non-destructive chemical measurement of a solution.

Validation of Low-Cost Sensors in Measuring Real-Time PM10 Concentrations at Two Sites in Delhi National Capital Region.

In the present study, we assessed for the first time the performance of our custom-designed low-cost Particulate Matter (PM) monitoring devices (Atmos) in measuring PM10 concentrations. We examined the ambient PM10 levels during an intense measurement campaign at two sites in the Delhi National Capital Region (NCR), India. In this study, we validated the un-calibrated Atmos for measuring ambient PM10 concentrations at highly polluted monitoring sites. PM10 concentration from Atmos, containing laser scattering-based Plantower PM sensor, was comparable with that measured from research-grade scanning mobility particle sizers (SMPS) in combination with optical particle sizers (OPS) and aerodynamic particle sizers (APS). The un-calibrated sensors often provided accurate PM10 measurements, particularly in capturing real-time hourly concentrations variations. Quantile–Quantile plots (QQ-plots) for data collected during the selected deployment period showed positively skewed PM10 datasets. Strong Spearman’s rank-order correlations (rs = 0.64–0.83) between the studied instruments indicated the utility of low-cost Plantower PM sensors in measuring PM10 in the real-world context. Additionally, the heat map for weekly datasets demonstrated high R2 values, establishing the efficacy of PM sensor in PM10 measurement in highly polluted environmental conditions.

Textile Electrocardiogram (ECG) Electrodes for Wearable Health Monitoring.

Wearable health-monitoring systems should be comfortable, non-stigmatizing, and able to achieve high data quality. Smart textiles with electronic elements integrated directly into fabrics offer a way to embed sensors into clothing seamlessly to serve these purposes. In this work, we demonstrate the feasibility of electrocardiogram (ECG) monitoring with sewn textile electrodes instead of traditional gel electrodes in a 3-lead, chest-mounted configuration. The textile electrodes are sewn with silver-coated thread in an overlapping zig zag pattern into an inextensible fabric. Sensor validation included ECG monitoring and comfort surveys with human subjects, stretch testing, and wash cycling. The electrodes were tested with the BIOPAC MP160 ECG data acquisition module. Sensors were placed on 8 subjects (5 males and 3 females) with double-sided tape. To detect differences in R peak detectability between traditional and sewn sensors, effect size was set at 10% of a sample mean for heart rate (HR) and R-R interval. Paired student’s t-tests were run between adhesive and sewn electrode data for R-R interval and average HR, and a Wilcoxon signed-rank test was run for comfort. No statistically significant difference was found between the traditional and textile electrodes (R-R interval: t = 1.43, p > 0.1; HR: t = −0.70, p > 0.5; comfort: V = 15, p > 0.5).

Validity of an under-mattress sensor for objective sleep measurement in critically ill patients: a prospective observational study

BackgroundConsidering the adverse effects of sleep disturbance in critical care settings, accurate assessment could aid therapy; however, methodological inadequacies mean that no viable option is currently available. Research in healthy population has recently shown that a non-wearable sleep measurement device placed under the mattress of the bed could be beneficial in intensive care settings. Therefore, we aimed to validate this device compared with polysomnography (PSG) and to assess how it related to subjective sleep evaluations.MethodsThis observational study measured the sleep of critically ill adult patients. The primary goal was to validate the Nemuri SCAN (NSCAN; Paramount Bed Co., Ltd., Tokyo, Japan) against the reference standard PSG for 24 h. The secondary goal was to evaluate the association between the objective parameters obtained from NSCAN and PSG and the subjective report data obtained using the Richards–Campbell Sleep Questionnaire (RCSQ) for the nighttime.ResultsEleven participants were evaluated. The median of the total sleep time scored by PSG was 456.0 (353.0–517.5) min during the nighttime and 305.0 (186.2–542.5) min during the daytime. PSG over 24 h revealed significant decreases in restorative sleep, with excessive daytime sleep, but with a normal quantity of nighttime sleep. The agreement, sensitivity, and specificity rates (with 95% confidence intervals) for the NSCAN compared with PSG were 68.4% (67.9–69.0%), 90.1% (89.7–90.6%), and 38.7% (37.9–39.7%), respectively. The median RCSQ value when subjectively evaluating nighttime sleep was 68.0 (26.3–83.5); this showed no correlation with the NSCAN sleep parameters, despite a positive correlation with the ratio of the stage N2 isolated or combined with restorative sleep in the PSG assessment.ConclusionsNSCAN had moderate agreement, high sensitivity, and poor specificity in intensive care settings, which is most likely due to its inability to identify immobile wakefulness often observed in critically ill patients or sleep depth. This remains a barrier to its use in the assessment of subjective sleep quality.Trial registrationThis investigation was part of an interventional trial registered with the University Hospital Medical Information Network Individual Clinical Trials Registry (UMIN000026350, http://www.umin.ac.jp/icdr/index-j.html) on March 1, 2017.

Autonomous Ion-Sensitive Field Effect Transistor-Based Total Alkalinity and pH Measurements on a Barrier Reef of Ka̅ne’ohe Bay

Here we present first of its kind high frequency Total Alkalinity (AT) and pH data from a single solid-state autonomous sensor collected during a 6-day deployment at a barrier reef in Kāneʻohe Bay on the CRIMP-2 buoy. This dual parameter sensor is capable of rapid (<60 s), near simultaneous measurement of the preferred seawater carbonate system parameters, pH and AT without requiring any external reagents or moving parts inherent to the sensor. Its solid state construction, low power consumption, and low titrated volume (nanoliters) requirement make this sensor ideal for in situ monitoring of the aqueous carbon dioxide system. Through signal averaging, we estimate the pH-AT sensor is capable of achieving 2-10 μmol kg-1 precision in AT and 0.005 for pH. The CRIMP-2 site in Hawaiʻi provided an excellent means of validation of the prototype pH-AT sensor due to the extensive observations routinely collected at this site and large daily fluctuations in AT (~116 μmol kg-1) driven primarily by high calcification...

Soft sensor validation for monitoring and resilient control of sequential subway indoor air quality through memory-gated recurrent neural networks-based autoencoders

Indoor air quality (IAQ) measurements play an important role in the subway ventilation system control, influencing over crucial factors as ventilation energy consumption and commuters’ health. Therefore, faulty sensors may result in misinterpreting the IAQ conditions and misoperating the air delivery rate level in subway stations. However, due to the IAQ data properties of dynamism and non-Gaussian distribution. Linear and fixed structures are not sufficient to extract essential features from the IAQ data. This paper presents a machine learning-based soft sensor validation technique to detect, diagnose, identify, and reconstruct faulty measurements of the multivariate IAQ data in subway stations. The proposed method is memory-gated recurrent neural networks-based autoencoders (MG-RNN-AE), which are capable of processing sequential and dynamic IAQ information. The performance of the sensor validation was evaluated through several metrics to consequently be compared among different methods, being the batch normalization-based gated recurrent unit (BN-GRU) method, the most effective to detect (DRSPE = 100%) and reconstruct faulty IAQ sensors (R2= 0.45-0.79). Additionally, the effects of the faulty and repaired measurements in the ventilation system were evaluated to determine that the proposed method is capable of finding a sustainable balance between energy demand and commuters’ health level.

Validation of a Sensor for Non-invasive Measurement of Stroke Volume and Cardiac Output

Validation of a Sensor for Non-invasive Measurement of Stroke Volume and Cardiac Output

Metamaterial sensor application concrete material reinforced with carbon steel fiber

In this paper, a rectangular split ring resonator-type metamaterial (MTM) sensor application is demonstrated in order to examine concrete materials. First, different types of concrete materials including carbon steel fiber with the purity ratio of 0.5%, 1% and 1.5% were prepared by using cement and water and their electrical properties were determined via Nicolson–Ross–Weir tehcnique. After that, compatible MTM-based sensor structure was designed and proposed. In order to find out the effect of the humidity on the concrete material, all samples were kept in the water pool for 28 days, the samples were then taken out and the temperature effect on the concrete materials was observed by increasing the heat up to 30[Formula: see text] and 70[Formula: see text] in the oven. The simulated resonance frequency shifts were observed at 910 MHz for concrete material sensor, 120 MHz for humidity sensor validation and 400 MHz for temperature sensor applications. By having large bandwidth in different fiber contents and validating the physical sensor applications as temperature and humidity, it was shown that the proposed study has novelty in the area of MTM-based sensor applications when it is compared with current state-of-the-art.

Validity of Instrumented 360° Turn Test in Older Adults with Cognitive Impairment

Aims: To examine concurrent and construct validity of inertial sensor 360° turn measures in relation with motion capture and mobility assessments in cognitively impaired older adults.Methods: Data was collected in 31 participants, mean age 85.2 (SD 5.2), during clockwise (CW) and counter clockwise (CCW) 360° turns using (1) APDM body-worn inertial sensors and (2) Qualisys 8-camera laboratory-based motion capture.Results: Absolute agreement between inertial sensor and motion capture measures was excellent for turn duration and turn peak velocity (ICC = 0.96–0.98). Strong to moderate correlations were present between inertial sensor turn measures and performance on the Timed Up and Go, Short Physical Performance Battery and 90-s Balance Test. ROC curve analysis of CCW 360° turn duration and turn peak velocity distinguished higher risk versus lower risk for mobility disability.Conclusions: Inertial sensor 360° turn measures demonstrated concurrent and construct validity in relation to motion capture and mobility assessments.