Linear Encoder Research Articles

Error Analysis of an Economical On-Site Calibration System for Linear Optical Encoders

A calibration system was designed to evaluate the accuracy of linear optical encoders at the micron level in a fast and economical manner. The system uses a commercial interferometer and motor stage as the calibrator and moving platform. Error analysis is necessary to prove the effectiveness and identify areas for optimization. A fixture was designed for the scale and interferometer target to meet the Abbe principle. A five-degree-of-freedom manual stage was utilized to adjust the reading head in optimal or suboptimal working conditions, such as working distance, offset, and angular misalignment. The results indicate that the calibration system has an accuracy of ±2.2 μm. The geometric errors of the calibration system, including mounting errors and non-ideal motions, are analyzed in detail. The system could be an inexpensive solution for encoder manufacturers and customers to calibrate a linear optical encoder or test its performance.

Understanding human–robot interaction forces: a new mechanical solution

Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues.

A Method for Reducing Sub-Divisional Errors in Open-Type Optical Linear Encoders with Angle Shift Pattern Main Scale

In this research, a novel approach is presented to enhance the precision of open-type optical linear encoders, focusing on reducing subdivisional errors (SDEs). Optical linear encoders are crucial in high-precision machinery. The overall error in optical linear encoders encompasses baseline error, SDE, and position noise. This study concentrates on mitigating SDEs, which are recurrent errors within each pitch period and arise from various contributing factors. A novel method is introduced to improve the quality of sinusoidal signals in open-type optical linear encoders by incorporating specially designed angle shift patterns on the main scale. The proposed method effectively suppresses the third order harmonics, resulting in enhanced accuracy without significant increases in production costs. Experimental results indicate a substantial reduction in SDEs compared to traditional methods, emphasizing the potential for cost-effective, high-precision optical linear encoders. This paper also discusses the correlation between harmonic suppression and SDE reduction, emphasizing the significance of this method in achieving higher resolutions in optical linear encoders.

A novel linear displacement sensor based on double-threshold decoding algorithm

Purpose Most of the linear encoders are based on optics. The accuracy and reliability of these encoders are greatly reduced in polluted and noisy environments. Moreover, these encoders have a complex structure and large sensor volume and are thus not suited to small application scenarios and do not have universality. This paper aims to present a new absolute magnetic linear encoder, which has a simple structure, small size and wide application range. Design/methodology/approach The effect of swing error is analyzed for the sensor structural arrangement. A double-threshold interval algorithm is then proposed to synthesize multiple interval electrical angles into absolute angles and convert them into actual displacement distances. Findings The final linear encoder measurement range is 15.57 mm, and the resolution reaches ± 2 µm. The effectiveness of the algorithm is demonstrated experimentally. Originality/value The linear encoder has good robustness, and high measurement accuracy, which is suitable for industrial production. The linear encoder has been mass-produced and used in an electric power-assisted braking system.

Validity and reliability of linear encoder muscle power testing in persons with Parkinson's disease

Objective To investigate the construct validity ON medication and the reliability both ON and OFF medication of linear encoder muscle power testing in persons with Parkinson's disease (pwPD). Design A study using baseline data from one randomized controlled trial (study 1) and one cohort study (study 2). Setting University exercise lab. Participants Study 1: 35 healthy controls and 70 pwPD. Study 2: 20 pwPD. Intervention Study 1: baseline data. Study 2: 4 chair rise tests (2 ON and 2 OFF medication), in a randomized order, separated by 4 to 16 days. Main measures Linear encoder data were collected from a chair rise test. Known groups validity and convergent validity (i.e., construct validity) were assessed by comparing peak power between pwPD and healthy controls and associations between peak power and functional performance (i.e., 6-Min Walk Test, Timed Up and Go Test, Six-Spot Step Test), respectively. Reliability was assessed as day-to-day variation and by intraclass correlation coefficients. Results Peak power was comparable between pwPD and healthy controls (−7.2%, p = 0.17), but lower in moderately impaired pwPD compared to mildly impaired pwPD (−27%, p < 0.01) and healthy controls (−23%, p < 0.01). Moderate to strong associations were observed between peak power and functional performance (r2 = 0.44–0.51). Day-to-day variation ON and OFF medication were 1.0 and 1.3 W/kg, respectively, while intraclass correlation coefficients were 0.95 (0.87;0.98) and 0.93 (0.82;0.97), respectively. Conclusion Linear encoder muscle power testing shows inconsistent known groups validity, acceptable convergent validity ON medication, and excellent day-to-day reliability ON and OFF medication in pwPD.

Deep Learning-Based Positioning Error Fault Diagnosis of Wire Bonding Equipment and an Empirical Study for IC Packaging

Little research has been done for artificial intelligence applications of semiconductor backend. This study aims to develop a deep learning based fault diagnosis framework as prognostics and health management (PHM) solutions with a comprehensive analytics process. A linear encoder sensor is employed to measure position, while data preparation is conducted to convert position information into a signal. Then, signal processing is used to extract the features, in which high pass filter is applied to normalize the signal and emphasize the features. High-dimensional features including time domain statistical features, time-frequency domain features obtained by continuous wavelet transform (CWT), and frequency domain features converted by fast Fourier transform (FFT) are extracted to prepare the dataset. An ensemble neural network model that integrates deep neural network (DNN) and convolutional neural network (CNN) is employed to recognize the pattern and diagnose the positioning errors. The accuracy and false alarm rate are considered to support maintenance decisions. An empirical study was conducted in a world leading IC assembly and testing company for validation. The results have shown that the proposed approach can effectively detect inappropriate installation of the bond head in wire bonding equipment for predictive maintenance and cost reduction.

Correlation between Power Elbow Flexion and Physical Performance Test: A Potential Predictor for Assessing Physical Performance in Older Adults.

With the increasing number of older adults and their declining motor and cognitive function, it is crucial to find alternative methods for assessing physical functionality. The Short Physical Performance Battery (SPPB), the Time Up and Go (TUG) test, the 4 Meter Walk Test and the Barthel Index (BI) have been used to evaluate mobility and fragility and predict falls. But some of these functional test tasks could be difficult to perform for frail older adults or bedridden patients that cannot ambulate. This study aimed to evaluate the relationship between these functional tests and the power elbow flexion (PEF test). A correlation study was designed with 41 older adults over 65 years of age. The upper limb muscle power was measured using a linear encoder (VITRUBE VBT) with the flexion of the elbow. Strong correlations were found between the PEF test and the 4mWT (rho = 0.715, p = 0.001) and TUG (rho= -0.768, p = 0.001), indicating that the greater the upper limb muscle power is, the greater physical performance will be. Moderate correlations were also found between the PEF and Barthel Index (rho = 0.495, p = 0.001) and SPPB (rho = 0.650, p < 0.001). There is a strong correlation between PEF and the functional tests, proving that older adults that have greater upper limb muscle power have better physical performance. Upper limb muscle power and PEF could be an interesting tool for the assessment of physical performance in bedridden older adults.

Methods for the Automated Determination of Sustained Maximum Amplitudes in Oscillating Signals

Abstract Machine condition monitoring has been proven to reduce machine downtime and increase productivity. The state-of-the-art research uses vibration monitoring for tasks such as maintenance and tool wear prediction. A less explored aspect is how vibration monitoring might be used to monitor equipment sensitive to vibration. In a manufacturing environment, one example of where this might be needed is in monitoring the vibration of optical linear encoders used in high-precision machine tools and coordinate measuring machines. Monitoring the vibration of sensitive equipment presents a unique case for vibration monitoring because an accurate calculation of the maximum sustained vibration is needed, as opposed to extracting trends from the data. To do this, techniques for determining sustained peaks in vibration signals are needed. This work fills this gap by formalizing and testing methods for determining sustained vibration amplitudes. The methods are tested on simulated signals based on experimental data. Results show that processing the signal directly with the novel Expire Timer method produces the smallest amounts of error on average under various test conditions. Additionally, this method can operate in real-time on streaming vibration data.

Robust neural tracking of linguistic speech representations using a convolutional neural network

Objective. When listening to continuous speech, populations of neurons in the brain track different features of the signal. Neural tracking can be measured by relating the electroencephalography (EEG) and the speech signal. Recent studies have shown a significant contribution of linguistic features over acoustic neural tracking using linear models. However, linear models cannot model the nonlinear dynamics of the brain. To overcome this, we use a convolutional neural network (CNN) that relates EEG to linguistic features using phoneme or word onsets as a control and has the capacity to model non-linear relations. Approach. We integrate phoneme- and word-based linguistic features (phoneme surprisal, cohort entropy (CE), word surprisal (WS) and word frequency (WF)) in our nonlinear CNN model and investigate if they carry additional information on top of lexical features (phoneme and word onsets). We then compare the performance of our nonlinear CNN with that of a linear encoder and a linearized CNN. Main results. For the non-linear CNN, we found a significant contribution of CE over phoneme onsets and of WS and WF over word onsets. Moreover, the non-linear CNN outperformed the linear baselines. Significance. Measuring coding of linguistic features in the brain is important for auditory neuroscience research and applications that involve objectively measuring speech understanding. With linear models, this is measurable, but the effects are very small. The proposed non-linear CNN model yields larger differences between linguistic and lexical models and, therefore, could show effects that would otherwise be unmeasurable and may, in the future, lead to improved within-subject measures and shorter recordings.

Devices to measure calf raise test outcomes: A narrative review.

The calf raise test (CRT) is commonly administered without a device in clinics to measure triceps surae muscle function. To standardise and objectively quantify outcomes, researchers use research-grade or customised CRT devices. To incorporate evidence-based practice and apply testing devices effectively in clinics, it is essential to understand their design, applicability, psychometric properties, strengths, and limitations. Therefore, this review identifies, summarises, and critically appraises the CRT devices used in science. Four electronic databases were searched in April 2022. Studies that used devices to measure unilateral CRT outcomes (i.e., number of repetitions, work, height) were included. Thirty-five studies met inclusion, from which seven CRT devices were identified. Linear encoder (n=18) was the most commonly used device, followed by laboratory equipment (n=6) (three-dimensional motion capture and force plate). These measured the three CRT outcomes. Other devices used were electrogoniometer, Häggmark and Liedberg light beam device, Ankle Measure for Endurance and Strength (AMES), Haberometer, and custom-made. Devices were mostly used in healthy populations or Achilles tendon pathologies. AMES, Haberometer, and custom-made devices were the most clinician-friendly, but only quantified repetitions were completed. In late 2022, a computer vision mobile application appeared in the literature and offered clinicians a low-cost, research-grade alternative. This review details seven devices used to measure CRT outcomes. The linear encoder is the most common in research and quantifies all three CRT outcomes. Recent advances in computer-vision provide a low-cost research-grade alternative to clinicians and researchers via a n iOS mobile application.

Speed Matters in Nordic Hamstring Exercise: Higher Peak Knee Flexor Force during Fast Stretch-Shortening Variant Compared to Standard Slow Eccentric Execution in Elite Athletes.

Hamstring strain injuries are prevalent in many sports. Research has demonstrated that the Nordic hamstring exercise (NHE), a knee-dominant exercise addressing the posterior chain muscles, can aid in reducing the risk of hamstring injuries in athletes. However, most research on hamstring injury prevention has focused on performing the eccentric version of the NHE (NHEECC). In contrast, in sports, it is quite frequent for athletes to use an eccentric-concentric version of the NHE. Additionally, eccentric NHE is typically performed using a slow, controlled tempo. The effect of a fast stretch-shortening cycle NHE (NHESSC) compared to standard slow NHEECC on peak knee flexor force has not been investigated. The aim of the study was therefore to investigate fast NHESSC vs. standard slow NHEECC. Our hypothesis posited that peak knee flexor force would be greater for fast NHESSC compared with standard slow NHEECC. The study involved 22 elite athletes (actively competing in both national and international events) consisting of female (n = 10) and male (n = 7) track and field athletes and male football players (n = 5), aged 17-31 years. The participants performed maximum trials of slow NHEECC and fast NHESSC repetitions in which measurement of bilateral peak knee flexor force was conducted at the ankle with the use of a load cell. During the NHEs, a linear encoder was used to measure both the position where the peak knee flexor force was recorded and the average eccentric velocity. SSC contributed to an enhanced NHE performance, where bilateral absolute peak knee flexor force was 13% higher for fast NHESSC vs. standard slow NHEECC (822 vs. 726 N, p < 0.01, ES = 0.54). Participants achieved a 32% greater forward distance at the breakpoint stage during NHEECC compared to the coupling phase for NHESSC (54 vs. 41 cm, p < 0.001, ES = 1.37). Eccentric average velocity was more than three times higher for NHESSC compared with NHEECC (0.38 vs. 0.12 m/s, p < 0.001, ES = 3.25). The key findings of this study were that SSC contributed to an enhanced NHE performance, where absolute peak knee flexor force was 13% greater for fast NHESSC compared to standard slow NHEECC. The fast NHESSC could therefore be an interesting alternative to the standard slow NHEECC execution, as it may offer potential advantages for sprint performance, as well as hamstring injury prevention and rehabilitation.

Design and Control of a Multiple-Section Continuum Robot With a Hybrid Sensing System

After decades of development, the technology of continuum robots continues to mature gradually and is used for various applications, e.g., inspection and repair in high-value-added industries, such as aerospace and nuclear. However, such robots are invariably designed with a hyper-redundant structure which causes condition-dependent uncertainties and errors in practical operations. In this article, a hybrid sensing solution—consisting of a dual displacement sensor system (linear and rotary encoders) and a self-carried visual tracking system—is presented to improve the control performance of a multisection cable-driven continuum robot. The dual displacement sensor system works to measure the cable-displacement error at the proximal end of the arm and predicts the cable elongation in the arm to eliminate the control error of the robot in joint-space via a new two-stage cable-displacement control approach. Simultaneously, the self-carried visual system provides real-time section-by-section tip tracking to improve the controllability of the arm in the task space. This feedback is then integrated with a two-level closed-loop controller to achieve accurate tip-positioning control. A series of validation experiments are carried out to validate the approach. Compared with an off-the-shelf position tracking system, the measurement error of the proposed self-carried visual tracking system is smaller than 2 mm, with a mean error of 0.67 mm, within the workspace of a single-section continuum robot. The distal-tip control accuracy of a two-section robot can achieve 1.72 mm under the closed-loop controller supported by the hybrid sensing system.

Development of an ultrasonic linear encoder

PurposeIn this investigation, a linear encoder system based on the ultrasonic transducer has been proposed. Ultrasonic transducers are usually designed for distance measurements, such as the time of flight method and sonar system. These applications are defined as discrete-length measurement technologies. The purpose of this study is to develop a continuous displacement measurement system using ultrasonic transducers.Design/methodology/approachA modified signal processing based on heterodyne signaling is implemented in this system. In the proposed signal processing, there is an automatic gain control module, a phase-shifting module, a phase detection module, an interpolation module and especially a frequency multiplication module, which can enhance the resolution and reduce the interpolation error simultaneously.FindingsThe proposed system can generate the encoding signals and is compatible with most motion control systems. For the experimental result, the maximum measurement error and standard deviation are about −0.027 and 0.048 mm, respectively. It shows that the proposed encoder system has the potential for displacement measurement tasks.Originality/valueThis study reveals an ultrasonic linear encoder that is capable of generating an incremental encoding signal, accompanied by a corresponding signal processing methodology. In contrast to the conventional heterodyne signal processing approach, the proposed multiplication method effectively reduces the interpolation error that arises because of multiple reflections.

Personalizing Resistance Training Mitigates Neuromuscular and Perceived Fatigue: The Autoregulation Cluster Training Method

To compare predetermined and autoregulated resistance training sessions on velocity loss and perceived fatigue. Twenty-six resistance-trained men completed 3 sessions including the back-squat and bench-press exercises matched for load (75% of 1-repetition maximum), volume (24 repetitions), and total rest (240s). Sessions were randomly performed as traditionalset (TRA), 3 sets of 8 repetitions with 120-second interset rests; cluster interset-rest redistribution (IRR), 6 clusters of 4 repetitions with 48-second between-clusters rests; and autoregulation cluster training (ACT), a personalized combination of clusters, repetitions per cluster, and between-clusters rest regulated on a velocity loss threshold. The comparative effects were evaluated on velocity loss outputs measured with a linear encoder and perceived fatigue responses reported using a single-item scale. IRR and ACT induced less velocity loss than TRA (b = -2.09, P < .001). ACT also mitigated velocity loss more than IRR (b = -2.31, P < .001). The back squat resulted in greater velocity loss compared to the bench press (b = 1.83, P < .001). Perceived fatigue responses mirrored the pattern observed for the velocity loss outputs (IRR and ACT vs TRA: b = -0.64, P < .001; ACT vs IRR: b = -1.05, P < .001; back squat vs bench press: b = 0.46, P = .005). IRR and ACT reduced neuromuscular and perceived fatigue, likely due to their cluster-set structures' embedding frequent windows of interset rest. However, the ACT was overall more effective, presumably given its personalized structure.

Perception of Bar Velocity Loss in Resistance Exercises: Accuracy Across Loads and Velocity Loss Thresholds in the Bench Press

Velocity-based training is used to prescribe and monitor resistance training based on velocity outputs measured with tracking devices. When tracking devices are unavailable or impractical to use, perceived velocity loss (PVL) can be used as a substitute, assuming sufficient accuracy. Here, we investigated the accuracy of PVL equal to 20% and 40% relative to the first repetition in the bench-press exercise. Following a familiarization session, 26 resistance-trained men performed 4 sets of the bench-press exercise using 4 different loads based on their individual load-velocity relationships (∼40%-90% of 1-repetition maximum [1RM]), completed in a randomized order. Participants verbally reported their PVL at 20% and 40% velocity loss during the sets. PVL accuracy was calculated as the absolute difference between the timing of reporting PVL and the actual repetition number corresponding to 20% and 40% velocity loss measured with a linear encoder. Linear mixed-effects model analysis revealed 4 main findings. First, across all conditions, the absolute average PVL error was 1 repetition. Second, the PVL accuracy was not significantly different between the PVL thresholds (β = 0.16, P = .267). Third, greater accuracy was observed in loads corresponding to the midportion of the individual load-velocity relationships (∼50%-60% 1RM) compared with lighter (<50% 1RM, β = 0.89, P < .001) and heavier loads (>60% 1RM, 0.63 ≤ β ≤ 0.84, all P values < .001). Fourth, PVL accuracy decreased with consecutive repetitions (β = 0.05, P = .017). PVL can be implemented as a monitoring and prescription method when velocity-tracking devices are impractical or absent.

Multi-Planar Jump Performance in Speed Skating Athletes: Investigating Interlimb Differences in an Asymmetrical Sport

Elite speed skaters are exposed to asymmetric lower limb loading consequent to the unidirectional turns inherent to the sport. This presents a unique model to study the effects of sport-specific loading on interlimb differences in mechanical muscle function. This study, therefore, examined baseline interlimb asymmetries in multi-directional jump tests in elite speed skaters using a cross-sectional design. Thereafter, participants were monitored longitudinally using the bilateral countermovement jump (CMJ) to quantify interlimb differences in mechanical muscle function throughout a competitive season. Pre-season baseline testing included a single leg lateral jump (JumpLat) and a single leg forward horizontal jump (JumpHorz) attached to a robotic linear position encoder, along with a bilateral CMJ on a dual force plate system. From baseline, CMJ monitoring was conducted throughout the 24-week competitive season. Within-limb changes in right vs left CMJ concentric impulse (CMJCon) and eccentric deceleration impulse (CMJEcc) were assessed using a linear mixed effects model. No systematic interlimb differences were found at baseline (p = 0.33–0.98) and the between-test agreement in limb dominance was poor (Kappa = −0.17–0.33). Furthermore, there were no time effects observed for interlimb differences in CMJCon (fixed effect = 0.01 N*s) and a small decrease in CMJEcc (fixed effects = −0.35 N*s, p = 0.01). These data suggest that even in a sport with asymmetrical loading, interlimb differences in mechanical output remain stable at the group level. However, changes occurring at the individual athlete level may be occurring that are meaningful for performance and injury.

Higher Precision Encoder Using Hologram Scale

Semiconductor manufacturing equipment requires improvement of the accuracy by a linear encoder in a short measurement range. The error in the short range involves the interpolation error and other errors. Improvement in the interpolation error had already achieved in existing research. In contrast, this paper describes the development of a grid interferometer-type linear encoder using a hologram scale with excellent accuracy in a short measurement range. The developed encoder can achieve the error excluding interpolation error less than 10-6 magnitude per measurement range of 50 μm. In the development, error factors in the short-range measurement were examined. An equipment to identify the accuracy in this short-range measurement with high resolution and accuracy was then developed. Error analysis by the developed accuracy measurement equipment made it possible to improve a linear encoder accuracy. As a result, the accuracy of grid interferometer type linear encoder was able to reach at ±20 pm in the measurement range of 50 μm.

Image sensing with multilayer nonlinear optical neural networks

Optical imaging is commonly used for both scientific and technological applications across industry and academia. In image sensing, a measurement, such as of an object's position, is performed by computational analysis of a digitized image. An emerging image-sensing paradigm breaks this delineation between data collection and analysis by designing optical components to perform not imaging, but encoding. By optically encoding images into a compressed, low-dimensional latent space suitable for efficient post-analysis, these image sensors can operate with fewer pixels and fewer photons, allowing higher-throughput, lower-latency operation. Optical neural networks (ONNs) offer a platform for processing data in the analog, optical domain. ONN-based sensors have however been limited to linear processing, but nonlinearity is a prerequisite for depth, and multilayer NNs significantly outperform shallow NNs on many tasks. Here, we realize a multilayer ONN pre-processor for image sensing, using a commercial image intensifier as a parallel optoelectronic, optical-to-optical nonlinear activation function. We demonstrate that the nonlinear ONN pre-processor can achieve compression ratios of up to 800:1 while still enabling high accuracy across several representative computer-vision tasks, including machine-vision benchmarks, flow-cytometry image classification, and identification of objects in real scenes. In all cases we find that the ONN's nonlinearity and depth allowed it to outperform a purely linear ONN encoder. Although our experiments are specialized to ONN sensors for incoherent-light images, alternative ONN platforms should facilitate a range of ONN sensors. These ONN sensors may surpass conventional sensors by pre-processing optical information in spatial, temporal, and/or spectral dimensions, potentially with coherent and quantum qualities, all natively in the optical domain.

Uncertainty Evaluation in calibration of Engineer’s Steel Rulers and Measuring Tapes; GUM and Monte Carlo Methods

Engineer’s steel rulers and measuring tapes are considered versatile dimensional measuring tools for many industrial applications. Calibrations of these tools are carried out by comparing their scales with reference length standards. The reference standards can be geodetic baselines provided by a laser interferometer system or linear encoder that integrated in well-designed guideway. This work aims to study not only the calibration process for steel rulers and measuring tapes but also the affecting parameters on this process and the assessment of associated uncertainty by different evaluation methods. In this paper, a 1000 mm engineer’s steel ruler and 5000 mm measuring tape are calibrated. A calibration system of precise guideway provided by linear encoder of 1 µm resolution are used. Associated uncertainties have been estimated based on GUM and Monte Carlo Simulation (MCS) methods. The parameters that may affect the calibration processes are carefully studied through the uncertainty evaluation. Expanded uncertainties of about 20 µm and 80 µm for calibration of 1000 mm engineer’s steel ruler and 5000 mm measuring tape respectively are achieved.

Validity and Reliability of Inertial Measurement System for Linear Movement Velocity in Flywheel Squat Exercise.

The aim of this study was to examine the validity and reliability of an Inertial Measurement System integrated into a secondary pulley (IMS) for determining linear velocity during flywheel squat exercises. Thirty-one male participants who were highly experienced in a flywheel resistance exercise training performed flywheel squat exercises with three incremental loads, and mean velocity (MV), mean propulsive velocity (MPV) and max velocity (Vmax) of the exercises were simultaneously recorded with a validated linear encoder and the IMS, in two different sessions. Validity was analyzed using ordinary least products regression (OLP), Lin's concordance correlation coefficient (CCC), and Hedge's g for the values from the linear encoder and the IMS. Test-retest reliability was determined by coefficient of variation (CV), Intraclass correlation coefficient (ICC), and standard error of measurement (SEM). Results showed a high degree of validity (OLP intercept = -0.09-0.00, OLP slope = 0.95-1.04, CCC = 0.96-0.99, Hedge's g < 0.192, SEM = 0.04-0.08) and reliability (CV < 0.21%, ICC > 0.88, SEM < 0.08). These results confirm that the IMS provides valid and reliable measures of movement velocity during flywheel squat exercises.