Inertial Motion Capture System Research Articles

Experimental Comparison between 4D Stereophotogrammetry and Inertial Measurement Unit Systems for Gait Spatiotemporal Parameters and Joint Kinematics.

(1) Background: Traditional gait assessment methods have limitations like time-consuming procedures, the requirement of skilled personnel, soft tissue artifacts, and high costs. Various 3D time scanning techniques are emerging to overcome these issues. This study compares a 3D temporal scanning system (Move4D) with an inertial motion capture system (Xsens) to evaluate their reliability and accuracy in assessing gait spatiotemporal parameters and joint kinematics. (2) Methods: This study included 13 healthy people and one hemiplegic patient, and it examined stance time, swing time, cycle time, and stride length. Statistical analysis included paired samples t-test, Bland-Altman plot, and the intraclass correlation coefficient (ICC). (3) Results: A high degree of agreement and no significant difference (p > 0.05) between the two measurement systems have been found for stance time, swing time, and cycle time. Evaluation of stride length shows a significant difference (p < 0.05) between Xsens and Move4D. The highest root-mean-square error (RMSE) was found in hip flexion/extension (RMSE = 10.99°); (4) Conclusions: The present work demonstrated that the system Move4D can estimate gait spatiotemporal parameters (gait phases duration and cycle time) and joint angles with reliability and accuracy comparable to Xsens. This study allows further innovative research using 4D (3D over time) scanning for quantitative gait assessment in clinical practice.

Validity of the estimated angular information obtained using an inertial motion capture system during standing trunk forward and backward bending

BackgroundBending the trunk forward and backward while standing are common daily activities and can have various patterns. However, any dysfunction in these movements can considerably affect daily living activities. Consequently, a comprehensive evaluation of spinal motion during these activities and precise identification of any movement abnormalities are important to facilitate an effective rehabilitation. In recent years, with the development of measurement technology, the evaluation of movement patterns using an inertial motion capture system (motion sensor) has become easy. However, the accuracy of estimated angular information obtained via motion sensor measurements can be affected by angular velocity. This study aimed to compare the validity of estimated angular information obtained by assessing standing trunk forward and backward bending at different movement speeds using a motion sensor with a three-dimensional motion analysis system.MethodsThe current study included 12 healthy older men. A three-dimensional motion analysis system and a motion sensor were used for measurement. The participants performed standing trunk forward and backward bending at comfortable and maximum speeds, and five sensors were attached to their spine. Statistical analysis was performed using the paired t-test, intraclass correlation coefficient, mean absolute error, and multiple correlation coefficient.ResultsResults showed that the estimated angular information obtained using each motion sensor was not affected by angular velocity and had a high validity.ConclusionsTherefore, the angular velocity in this study can be applied clinically for an objective evaluation in rehabilitation.

Biceps femoris muscle-tendon strain during an entire overground sprint acceleration: a biomechanical explanation for hamstring injuries in the acceleration phase

ABSTRACT The objectives of this study were to analyse the peak muscle-tendon (MT) strain of the hamstring during an entire acceleration sprint overground and examine their relationship with relative joint angles and segment orientation in the sagittal plane, which are the direct causes of MT strain. Kinematic data were recorded using a 3D inertial motion capture system in 21 male semi-professional soccer players during 40-metre overground sprint. Scaled musculoskeletal models were used to estimate peak MT strain in the hamstring over 16 steps. Biceps femoris long head (BFLH) exhibited the largest peaks in MT strain compared to semitendinosus (ST) and semimembranosus (SM) muscles across all the steps, with its overall strain decreased as the number of steps and maximum speed increased. Hip flexion angle was found to be a strong predictor (p < 0.001) of joint angles, being the orientation of the pelvis in the sagittal plane of the segment with the greatest influence (p < 0.001) on the peak MT strain of BFLH during sprinting. The current study provides a biomechanical explanation for the high proportion of hamstring injuries in the acceleration phase of sprinting.

Multimodal Embodiment Research of Oral Music Traditions: Electromyography in Oud Performance and Education Research of Persian Art Music

With the recent advent of research focusing on the body’s significance in music, the integration of physiological sensors in the context of empirical methodologies for music has also gained momentum. Given the recognition of covert muscular activity as a strong indicator of musical intentionality and the previously ascertained link between physical effort and various musical aspects, electromyography (EMG)—signals representing muscle activity—has also experienced a noticeable surge. While EMG technologies appear to hold good promise for sensing, capturing, and interpreting the dynamic properties of movement in music, which are considered innately linked to artistic expressive power, they also come with certain challenges, misconceptions, and predispositions. The paper engages in a critical examination regarding the utilisation of muscle force values from EMG sensors as indicators of physical effort and musical activity, particularly focusing on (the intuitively expected link to) sound levels. For this, it resides upon empirical work, namely practical insights drawn from a case study of music performance (Persian instrumental music) in the context of a music class. The findings indicate that muscle force can be explained by a small set of (six) statistically significant acoustic and movement features, the latter captured by a state-of-the-art (full-body inertial) motion capture system. However, no straightforward link to sound levels is evident.

Ergonomic Analysis of Dental Work in Different Oral Quadrants: A Motion Capture Preliminary Study among Endodontists.

Dentists, including endodontists, frequently experience musculoskeletal disorders due to unfavourable working postures. Several measures are known to reduce the ergonomic risk; however, there are still gaps in the research, particularly in relation to dental work in the different oral regions (Quadrants 1-4). In this study (of a pilot character), a total of 15 dentists (8 male and 7 female) specialising in endodontics were measured while performing root canal treatments on a phantom head. These measurements took place in a laboratory setting using an inertial motion capture system. A slightly modified Rapid Upper Limb Assessment (RULA) coding system was employed for the analysis of kinematic data. The significance level was set at p = 0.05. The ergonomic risk for the entire body was higher in the fourth quadrant than in the first quadrant for 80% of the endodontists and higher than in the second quadrant for 87%. For 87% of the endodontists, the ergonomic risk for the right side of the body was significantly higher in the fourth quadrant compared to the first and second quadrant. The right arm was stressed more in the lower jaw than in the upper jaw, and the neck also showed a greater ergonomic risk in the fourth quadrant compared to the first quadrant. In summary, both the total RULA score and scores for the right- and lefthand sides of the body ranged between 5 and 6 out of a possible 7 points. Considering this considerable burden, heightened attention, especially to the fourth quadrant with a significantly higher ergonomic risk compared to Quadrants 1 and 2, may be warranted.

Estimating Compressive and Shear Forces at L5-S1: Exploring the Effects of Load Weight, Asymmetry, and Height Using Optical and Inertial Motion Capture Systems.

This study assesses the agreement of compressive and shear force estimates at the L5-S1 joint using inertial motion capture (IMC) within a musculoskeletal simulation model during manual lifting tasks, compared against a top-down optical motion capture (OMC)-based model. Thirty-six participants completed lifting and lowering tasks while wearing a modified Plug-in Gait marker set for the OMC and a full-body IMC set-up consisting of 17 sensors. The study focused on tasks with variable load weights, lifting heights, and trunk rotation angles. It was found that the IMC system consistently underestimated the compressive forces by an average of 34% (975.16 N) and the shear forces by 30% (291.77 N) compared with the OMC system. A critical observation was the discrepancy in joint angle measurements, particularly in trunk flexion, where the IMC-based model underestimated the angles by 10.92-11.19 degrees on average, with the extremes reaching up to 28 degrees. This underestimation was more pronounced in tasks involving greater flexion, notably impacting the force estimates. Additionally, this study highlights significant differences in the distance from the spine to the box during these tasks. On average, the IMC system showed an 8 cm shorter distance on the X axis and a 12-13 cm shorter distance on the Z axis during lifting and lowering, respectively, indicating a consistent underestimation of the segment length compared with the OMC system. These discrepancies in the joint angles and distances suggest potential limitations of the IMC system's sensor placement and model scaling. The load weight emerged as the most significant factor affecting force estimates, particularly at lower lifting heights, which involved more pronounced flexion movements. This study concludes that while the IMC system offers utility in ergonomic assessments, sensor placement and anthropometric modeling accuracy enhancements are imperative for more reliable force and kinematic estimations in occupational settings.

Kinematic analysis of preparation for transferring from wheelchair to bed

ABSTRACT This study aimed to clarify the kinematics, particularly of the shoulder and hip joints, during preparation for manual wheelchair-to-bed transfer (i.e. when flipping up the arm and foot supports). This cross-sectional study included 32 able-bodied individuals. The kinematics of the shoulder and hip joints when the arm and foot supports were flipped up of manual wheelchair, were evaluated using a markerless inertial sensor-based motion capture system. We found that flipping the arm support upwards involved a large amount of abduction, internal and external rotation, flexion, and extension at the shoulder joint, whereas flipping the foot support upwards involved a large amount of flexion at the hip joint. The findings suggest that it is necessary to consider the range of motion required to flip up the arm and foot supports of manual wheelchairs, particularly in those with limited shoulder and hip range of motion such as older people, neuromuscular disorders, and orthopedic disorders.

Can single-use versus standard duodenoscope improve ergonomics in ERCP? A comparative, simulation-based pilot study.

Background and study aims Musculoskeletal disorders (MSDs) and injuries (MSIs) are frequent in gastrointestinal endoscopy. The aim of this study was to assess potential ergonomic advantages of a lighter single-use duodenoscope compared with a standard reusable one for endoscopists performing endoscopic retrograde cholangiopancreatography (ERCP). Methods Three experienced endoscopists performed an ergonomic, preclinical, comparative protocol-guided simulation study of a single-use and a standard reusable duodenoscope using an anatomic bench model. Surface EMG signals from left forearm and arm muscles were recorded. A commercial inertial sensor-based motion capture system was applied to record body posture as well. Results A significant lowering of root mean square amplitude and amplitude distribution of biceps brachii signal (ranging from 13% to 42%) was recorded in all the participants when using a single-use duodenoscope compared with a reusable one. An overall reduction of muscle activation amplitude and duration was also associated with the single-use duodenoscope for forearm muscles, with different behaviors among subjects. Participants spent most of the time in wrist extension (> 80%) and ulnar deviation (> 65%). A consistent pattern of functional range of motion employed for completing all procedures was observed. Conclusions Our study showed that a lighter scope has a promising effect in reducing upper arm muscle activity during ERCP with potential benefit on musculoskeletal health in the ERCP setting.

Understanding Musculoskeletal Loadings among Supermarket Checkout Counter Cashiers: A Biomechanical Analysis

Work-related musculoskeletal disorders (WMSD) are highly prevalent among supermarket cashiers. These disorders are frequently related to the adoption of awkward postures and manual materials handling. This study aimed to analyze musculoskeletal loadings in supermarket cashiers, considering the handling of different products and different checkout conditions. To accomplish this, we employed an inertial motion capture system to measure full-body kinematics while simulating 19 cashier tasks. The study included five female cashiers from a supermarket in Northern Portugal, ranging in age from 19 to 61 years old. Using joint angles, material load, and muscle function as input parameters, we conducted the musculoskeletal loadings assessment using the Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA) methods. Results showed that RULA scores were higher for the microtasks that involved product scanning. Regarding microstasks analyzed by REBA, the replacement of paper rolls for the receipt machine at the checkout counter yields the highest scores. Based on these findings, there is a compelling need to redesign supermarket checkout workstations to alleviate the physical demands placed on cashiers and to ensure organizational sustainability.

A Low-Cost Inertial Measurement Unit Motion Capture System for Operation Posture Collection and Recognition.

In factories, human posture recognition facilitates human-machine collaboration, human risk management, and workflow improvement. Compared to optical sensors, inertial sensors have the advantages of portability and resistance to obstruction, making them suitable for factories. However, existing product-level inertial sensing solutions are generally expensive. This paper proposes a low-cost human motion capture system based on BMI 160, a type of six-axis inertial measurement unit (IMU). Based on WIFI communication, the collected data are processed to obtain the displacement of human joints' rotation angles around XYZ directions and the displacement in XYZ directions, then the human skeleton hierarchical relationship was combined to calculate the real-time human posture. Furthermore, the digital human model was been established on Unity3D to synchronously visualize and present human movements. We simulated assembly operations in a virtual reality environment for human posture data collection and posture recognition experiments. Six inertial sensors were placed on the chest, waist, knee joints, and ankle joints of both legs. There were 16,067 labeled samples obtained for posture recognition model training, and the accumulated displacement and the rotation angle of six joints in the three directions were used as input features. The bi-directional long short-term memory (BiLSTM) model was used to identify seven common operation postures: standing, slightly bending, deep bending, half-squatting, squatting, sitting, and supine, with an average accuracy of 98.24%. According to the experiment result, the proposed method could be used to develop a low-cost and effective solution to human posture recognition for factory operation.

American Sign Language Recognition and Translation Using Perception Neuron Wearable Inertial Motion Capture System.

Sign language is designed as a natural communication method to convey messages among the deaf community. In the study of sign language recognition through wearable sensors, the data sources are limited, and the data acquisition process is complex. This research aims to collect an American sign language dataset with a wearable inertial motion capture system and realize the recognition and end-to-end translation of sign language sentences with deep learning models. In this work, a dataset consisting of 300 commonly used sentences is gathered from 3 volunteers. In the design of the recognition network, the model mainly consists of three layers: convolutional neural network, bi-directional long short-term memory, and connectionist temporal classification. The model achieves accuracy rates of 99.07% in word-level evaluation and 97.34% in sentence-level evaluation. In the design of the translation network, the encoder-decoder structured model is mainly based on long short-term memory with global attention. The word error rate of end-to-end translation is 16.63%. The proposed method has the potential to recognize more sign language sentences with reliable inertial data from the device.

Individual differences in children's movement variability in a virtual reality playground task

Children's movements are highly complex, and thus require measurements that capture various gross motor strategies. This study examined whether aspects of individual differences in children's gross motor movement patterns could be captured in virtual reality (VR) and how motor movements could be conceptualized through freezing-freeing patterns of degrees of freedom. To this end, a three-minute VR scenario was developed for children to freely explore, play, and move around without further instructions, and their movement strategies were simultaneously captured by a non-invasive inertial motion capture system. Sixty-four children aged 7–10 (boys: n = 37, girls: n = 27) participated. The results of correlational and principal component analysis (PCA) on measures of variability of upper extremities indicated significant relationships between nearly all measures (r = 0.31–0.69, p < 0.05). Similarly, a PCA on variability from joint movements in the lower extremities indicated relatively high intercorrelations (r = 0.31–0.71, p < 0.01). A pattern of four different variability profiles was indicated in the interrelationship between the upper and lower body. These findings emphasize the value of using innovative measurements and whole-body motion capture to disentangle individual differences in children's movement variability in product- and process-oriented assessments of gross motor competence.

Utilizing Motion Capture Systems for Instrumenting the OCRA Index: A Study on Risk Classification for Upper Limb Work-Related Activities.

In the search to enhance ergonomic risk assessments for upper limb work-related activities, this study introduced and validated the efficiency of an inertial motion capture system, paired with a specialized platform that digitalized the OCRA index. Conducted in a semi-controlled environment, the proposed methodology was compared to traditional risk classification techniques using both inertial and optical motion capture systems. The inertial method encompassed 18 units in a Bluetooth Low Energy tree topology network for activity recording, subsequently analyzed for risk using the platform. Principal outcomes emphasized the optical system's preeminence, aligning closely with the conventional technique. The optical system's superiority was further evident in its alignment with the traditional method. Meanwhile, the inertial system followed closely, with an error margin of just ±0.098 compared to the optical system. Risk classification was consistent across all systems. The inertial system demonstrated strong performance metrics, achieving F1-scores of 0.97 and 1 for "risk" and "no risk" classifications, respectively. Its distinct advantage of portability was reinforced by participants' feedback on its user-friendliness. The results highlight the inertial system's potential, mirroring the precision of both traditional and optical methods and achieving a 65% reduction in risk assessment time. This advancement mitigates the need for intricate video setups, emphasizing its potential in ergonomic assessments.

Biomechanical Analysis of Golf Swing Motion Using Hilbert-Huang Transform.

In golf swing analysis, high-speed cameras and Trackman devices are traditionally used to collect data about the club, ball, and putt. However, these tools are costly and often inaccessible to golfers. This research proposes an alternative solution, employing an affordable inertial motion capture system to record golf swing movements accurately. The focus is discerning the differences between motions producing straight and slice trajectories. Commonly, the opening motion of the body's left half and the head-up motion are associated with a slice trajectory. We employ the Hilbert-Huang transform (HHT) to examine these motions in detail to conduct a biomechanical analysis. The gathered data are then processed through HHT, calculating their instantaneous frequency and amplitude. The research found discernible differences between straight and slice trajectories in the golf swing's moment of impact within the instantaneous frequency domain. An average golfer, a single handicapper, and three beginner golfers were selected as the subjects in this study and analyzed using the proposed method, respectively. For the average golfer, the head and the left leg amplitudes of the swing motions increase at the moment of impact of the swings, resulting in the slice trajectory. These results indicate that an opening of the legs and head-up movements have been detected and extracted as non-linear frequency components, reviewing the biomechanical meaning in slice trajectory motion. For the single handicapper, the hip and left arm joints could be the target joints to detect the biomechanical motion that triggered the slice trajectory. For the beginners, since their golf swing forms were not finalized, the biomechanical motions regarding slice trajectory were different from each swing, indicating that beginner golfers need more practice to fix their golf swing form first. These results revealed that our proposed framework applied to different golf levels and could help golfers to improve their golf swing skills to achieve straight trajectories.

Wavelet-ARMA-Based Short-Term Drift Calibration of IMU Position on Human Lower Limbs

Position calibration in the inertial motion capture (Mocap) system is a crux to guarantee the correct calculation of human posture. Due to muscle movement and clothes slippage during motion, the position of inertial measurement units (IMUs) installed on the human body generates displacements. Aiming at the drift error caused by IMUs’ position shift in the short term, this paper proposes a wavelet-ARMA prediction model. Three different wavelet bases, Haar, Daubechies, and Coiflet, are selected to combine with the ARMA model to predict angle sequences, among which the Db4 wavelet-ARMA model with the best prediction performance, choosing the angle sequence predicted by the model and the measurement sequence to set up an error model, and using the Gauss-Newton (GN) and the dynamic weight particle swarm optimization (DWPSO) algorithms to realize IMUs’ position calibration. The experimental results show that the wavelet-ARMA model has better prediction performance than the ARMA, BP, and LSTM models with the value of the calibrated RMSE decreasing. The results confirm that the model proposed in this paper can accurately predict the changing trend of joint angle sequences on human lower limbs during gait motion and automatically calibrate the short-term drift error formed in the process of gait motion.

Application of mobile sensors based on deep neural networks in sports psychological detection and prevention

This article proposes a low-power, low-cost, programmable neural network processor for IoT applications. Aiming at the human inertial motion capture system, a human motion sensor detection method based on long- and short-term memory network is proposed. It provides a practical method for studying human motion detection based on mobile sensors and portable devices. Based on the research of human movement sensor detection method based on long and short-term memory network, this paper analyzes the current research status of sports psychological fatigue detection through the production mechanism, external performance, evidence and entertainment measures of sports psychological fatigue, in order to obtain a better solution. Quickly eliminate the mental fatigue of athletes. At the same time, improve and improve the physical and psychological functions of athletes of different qualities, and further improve sports performance. So far, the theoretical definition of sports mental fatigue and the operational definition of sports mental fatigue are still the center of discussion and research by sports psychologists. This article will also elaborate on the development of the most important concepts describing sports fatigue at home and abroad, using depth Neural network and mobile sensor technology have carried out research and exploration on the mental recognition of athletes in sports.

Effects of various hyperopia intervention levels on male college students' gait kinematics.

Background: Hyperopia is a common blurred vision phenomenon that affects postural control in gait; however, current research has focused on the alteration and correction of hyperopia's physiological characteristics, ignoring the effect of hyperopia on gait kinematic characteristics. The effect of hyperopia on the basic form of movement walking is a worthy concern. Objective: To investigate the gait kinematic characteristics of male college students with varying degrees of visual acuity (normal vision, hyperopia 150°, and hyperopia 450°), as well as to provide a theoretical foundation for the effect of visual acuity on gait and fall risk reduction. Methods: Twenty-two male college students with normal visual acuity were chosen. Their vision was tested using a standard visual acuity logarithm table at normal and with 150° and 450° concave lenses. Gait kinematic data were collected under normal vision and hyperopic conditions using the PN3 Pro advanced inertial motion capture system and Axis Studio application program. Results and conclusion: 1. The change of center of gravity in Pre-double support was smaller than normal vision; Late-single support and Late-swing was larger than normal vision; 2. The percentage of the double-leg support decreased; the percentage of the single-leg support and the Late-swing increased; 3. For the joints' range of motion, Trunk flexion and extension range of motion in Pre-single support, Late-double support and Pre-swing smaller than normal visual acuity, and Late-swing larger than normal; hip internal abduction and adduction and internal and external rotation are larger than normal vision in Late-single support; knee and ankle in abduction and adduction direction are larger than normal vision in the swing stage; hip flexion and extension, internal external rotation are larger than normal vision in the swing stage. Hyperopic interventions have an impact on the kinematic characteristics of gait in male college students, mainly in terms of altered balance, increased instability, increased difficulty in maintaining trunk stability, and increased risk of injury.

Do Mechatronic Poles Change the Gait Technique of Nordic Walking in Patients with Ischemic Heart Disease?

The study aimed to compare the technique of normal gait with the Nordic walking (NW) gait with classical and mechatronic poles in patients with ischemic heart disease. It was assumed that equipping classical NW poles with sensors enabling biomechanical gait analysis would not cause a change in the gait pattern. The study involved 12 men suffering from ischemic heart disease (age: 66.2 ± 5.2 years, body height: 173.8 ± 6.74 cm; body mass: 87.3 ± 10.89 kg; disease duration: 12.2 ± 7.5 years). The MyoMOTION 3D inertial motion capture system (Noraxon Inc., Scottsdale, AZ, USA) was used to collect biomechanical variables of gait (spatiotemporal and kinematic parameters). The subject's task was to cover the 100 m distance with three types of gait-walking without poles (normal gait), walking with classical poles to NW, and walking with mechatronic poles from the so-called preferred velocity. Parameters were measured on the right and left sides of the body. The data were analyzed using two-way repeated measures analysis of variance with the between-subject factor "body side." Friedman's test was used when necessary. For most kinematic parameters, with the exception of knee flexion-extension (p = 0.474) and shoulder flexion-extension (p = 0.094), significant differences were found between normal and walking with poles for both the left and right side of the body and no differences due to the type of pole. Differences between the left and right movement ranges were identified only for the ankle inversion-eversion parameter (gait without poles p = 0.047; gait with classical poles p = 0.013). In the case of spatiotemporal parameters, a reduction in the cadence step value using mechatronic poles and the stance phase using classical poles compared to normal walking was observed. There was also an increase in the values for step length and step time regardless of the type of poles, stride length, and swing phase when using classical poles and stride time when using mechatronic poles. The differences between the right and left sides of the measurement occurred when walking with both types of poles for single support (gait with classical poles p = 0.003; gait with mechatronic poles p = 0.030), stance phase (gait with classical poles p = 0.028; gait with mechatronic poles p = 0.017) and swing phase (gait with classical poles p = 0.028; gait with mechatronic poles p = 0.017). Mechatronic poles can be used in the study of the biomechanics of gait in real-time with feedback on its regularity because no statistically significant differences were found between the NW gait with classical and mechatronic poles in the studied men with ischemic heart disease.

Mass point versus whole-body modeling of skiers for performance evaluation in alpine skiing.

The altitude differential of the specific mechanical energy, , is used to evaluate skiing performance. It is defined as the negative differential between the skier's total specific mechanical energy ( ) and the altitude of the skier's center of mass (COM). Till now, was obtained upon a mass-point (MP) model of the skier's COM, which neither considered the segmental energies of their relative movements to the COM, nor their rotational kinetic energies. The aims of the study were therefore: (a) to examine the deviations in between the MP and a more complex linked segment (LS) skier model consisting of 15 rigid bodies, which encountered the aforementioned defectiveness, (b) to compare the energy fluctuations of the two skier models, and (c) to investigate the influence of the gate setup on (a) and (b) in giant slalom. Three-dimensional whole-body kinematics of nine skiers was measured using a global navigation satellite system and an inertial motion capture system while skiing on a predefined course divided into a turny and open gate setup. Mechanical energies including their altitude differentials were calculated for the LS and MP models. There were no significant differences in and ski turn averages, as in individual data points, between both skier models for both analyzed gate setups. The energies additionally considered by the LS model presented a negligible part regardless of the gate setup. In conclusion, the MP skier model is sufficiently accurate for the evaluation of the skiing performance with .

Measurement of Hand Joint Angle Using Inertial-Based Motion Capture System

The inertial sensor motion capture system has significant advantages over the classical optical motion capture system, including its high versatility, portability, and affordability. However, its accuracy is over one order of magnitude lower than the optical system. The measurement error of the finger joint angle is mainly due to sensor drift and misalignment of sensor to finger segment. In this article, we propose a method that includes both orientation estimation and calibration for accurate joint angle estimation. Specifically, at first, the accuracy of the sensor orientation is greatly improved using the square root cubature Kalman filter (SRCKF) to fuse the magnetic and inertial measurement units (MIMUs) data. Second, the kinematic restrictions of the finger joints are used for initial and in-process calibration to achieve sensor-to-segment (StoS) calibration throughout the process. Finally, the difference between the orientation of the two adjacent segments is the joint angle. Experiments show that our proposed system improves joint measurement accuracy compared with the existing inertial sensor-based systems. Evaluation of ten participants showed that the average root mean square error (RMSE) of finger joint measurements is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5.5^{\circ }(\pm 4.0^{\circ })$ </tex-math></inline-formula> . Our proposed system provides accurate information in measuring hand joint angles and quantifying hand movement function in clinical practice.