Progress on Range of Motion After Total Knee Replacement by Sensor-Based System

Research trends and frontiers in rehabilitation after total knee arthroplasty: based on bibliometric and visualization analysis

BACKGROUND

Total knee arthroplasty (TKA) is an effective treatment for end-stage knee osteoarthritis, and postoperative rehabilitation is crucial. However, a comprehensive bibliometric analysis of this area has yet to emerge. This study aims to visualize the research trends in postoperative rehabilitation after TKA through bibliometric analysis and explore current research frontiers and hotspots.

METHODS

Publications related to postoperative rehabilitation following TKA were identified and extracted from the Web of Science Core Collection (WoSCC) database. CiteSpace and VOSviewer were used for bibliometric and visualization analysis.

RESULTS

From January 1, 2000, to December 31, 2022, a total of 1,422 articles on TKA postoperative rehabilitation were identified from the database. The number of publications and citations showed steady growth during this period. The United States was the major contributor in this field, with the University of Colorado being the most active institution domestically. J Arthroplasty ranked first in both publication volume and total citations among all journals. Stevens-Lapsley, JE, and Mizner, RL were the two most influential authors. Reference and keyword analyses suggest that remote or home-based rehabilitation, the development of novel prehabilitation techniques, and pain management hold significant research potential, constituting current research hotspots.

CONCLUSION

This study quantitatively identified and assessed the current research status and trends in perioperative rehabilitation management for TKA through bibliometric and visualization analyses. It provides essential information for scholars in the field of TKA postoperative rehabilitation research, highlighting key research frontiers and trends.

A home-based tele-rehabilitation exercise system for patients after knee replacement surgery

BACKGROUND

Knee arthritis is a destructive disorder that affects the knee joints and causes pain and reduced mobility. Drug treatments, weight loss, and exercise control the symptoms of the disease, but these methods only delay the disease process and eventually, knee joint replacement surgery will be needed. After surgery, with the help of a proper physiotherapy program, full recovery takes an average of 6-12 months. However, currently, there is no similar tool to facilitate this process in Iran.

OBJECTIVE

The purpose of this research is to design and develop the prototype of a rehabilitation system for patients after knee replacement surgery, which provides patients with information and appropriate physiotherapy programs.

METHODS

This study was development-applied and was done in three stages. In the first stage, the needs and content of education and therapeutic exercises were prepared in the form of a checklist, and then the necessity of each item was checked in the evaluation sessions. In the second stage, the prototype of the system was developed using Adobe XD software and based on the requirements approved from the previous stage. In the third stage, the usability of the program was analyzed from the point of view of experts using the exploratory evaluation method with Nielsen's 13 principles of usability.

RESULTS

At first, the system requirements were extracted and prepared in two checklists of content (51 exercises) and capabilities (60 items). Then after a survey of experts based on the Delphi technique, content information (43 exercises) and functional and non-functional requirements (53 items) were obtained. A survey of experts helped to finalize the information elements, categorize them, and prepare the final version of the checklists. Based on this, the system requirements were classified into 11 categories, and the training content was classified into 3 training periods. Finally, the design and development of the system was done. This system has admin, physician, and patient user interfaces. The result of usability showed that this system is efficient and there are only a few problems in the feature of helping users to detect and recover from errors.

CONCLUSION

It seems necessary to develop a system based on the principles of usability by therapists and rehabilitation specialists to train and monitor the remote rehabilitation process of patients after knee joint replacement at home. And the importance of involving stakeholders in the design and development of remote rehabilitation systems is not hidden from anyone. Kara system has all of the above.

Retracted Article: Validity and Reliability of Sensor-based Measures of Lower Limb Range of Motion in Soccer Players: a Cross-sectional Study

Ein Defizit der Beweglichkeit gilt als Risikofaktor für Verletzungen der unteren Extremität im Fußball. Zur Messung des Bewegungsausmaßes (Range of Motion [ROM]) eines Gelenks werden analoge Goniometer verwendet. Zunehmend entwickelte sensorbasierte Verfahren wurden hinsichtlich ihrer Testgüte noch nicht hinreichend untersucht. Ziel dieser Studie war die Bestimmung der Übereinstimmungsvalidität sowie der Intratester- und Intertester-Reliabilität sensorbasierter Messungen des Bewegungsumfangs der unteren Extremität bei Fußballspielern. 36 beschwerdefreie Amateurfußballer (Alter: 26,3 ± 4,7 Jahre) wurden in die Studie eingeschlossen. Aus 5 Physiotherapeuten wurden 3 zufällig bestimmt, um die Messungen durchzuführen. Zwei Tester führten die Messungen (1. ROM Knie aus Langsitz; 2. Streckdefizit Knie aus Langsitz; 3. ROM Knie aus Stand; 4. ROM Sprunggelenk Dorsalextension [DE] während Ausfallschritt; 5. ROM Sprunggelenk Plantarflexion [PF] aus Sitz auf dem Stuhl) mit dem digitalen Sensor durch (Index-Test). Der 3. Tester übernahm die Messungen mit dem analogen Goniometer nach Neutral-Null-Methode mit den Probanden in Rückenlage (Referenzstandard). Zur statistischen Analyse wurden der Pearson-Korrelationskoeffizient r, Bland-Altman-Analysen (BAA) und der Intraklassenkorrelationskoeffizient (ICC) verwendet (p ≤ 0,05). Nur bei den Messungen 4 und 5 zeigten sich in der BAA akzeptable mittlere Differenzen von 8,4° (DE) und −10,2° (PF). Bei Messung 1 lag eine moderate Korrelation (r = 0,582) vor. Die sensorbasierten Messungen des Bewegungsumfangs des Knie- und Sprunggelenks wiesen eine exzellente Intra- und Intertesterreliabilität auf (ICC = 0,949–0,986; ICC = 0,895–0,968). Mit dem hier verwendeten etablierten Referenzstandard zeigten sie jedoch nur eine eingeschränkte Übereinstimmung, was mit den unterschiedlichen Ausgangspositionen von Index-Test und Referenzstandard erklärt werden kann.

Three-Dimensional Human Posture Recognition by Extremity Angle Estimation with Minimal IMU Sensor

Recently, posture recognition technology has advanced rapidly. Herein, we present a novel posture angle calculation system utilizing a single inertial measurement unit and a spatial geometric equation to accurately identify the three-dimensional (3D) motion angles and postures of both the upper and lower limbs of the human body. This wearable system facilitates continuous monitoring of body movements without the spatial limitations or occlusion issues associated with camera-based methods. This posture-recognition system has many benefits. Providing precise posture change information helps users assess the accuracy of their movements, prevent sports injuries, and enhance sports performance. This system employs a single inertial sensor, coupled with a filtering mechanism, to calculate the sensor's trajectory and coordinates in 3D space. Subsequently, the spatial geometry equation devised herein accurately computed the joint angles for changing body postures. To validate its effectiveness, the joint angles estimated from the proposed system were compared with those from dual inertial sensors and image recognition technology. The joint angle discrepancies for this system were within 10° and 5° when compared with dual inertial sensors and image recognition technology, respectively. Such reliability and accuracy of the proposed angle estimation system make it a valuable reference for assessing joint angles.

Mobile and Computer-Based Applications for Rehabilitation Monitoring and Self-Management After Knee Arthroplasty: Scoping Review

BACKGROUND

Successful post-knee replacement rehabilitation requires adequate access to health information, social support, and periodic monitoring by a health professional. Mobile health (mHealth) and computer-based technologies are used for rehabilitation and remote monitoring. The extent of technology use and its function in post-knee replacement rehabilitation care in low and middle-income settings are unknown.

OBJECTIVE

To inform future mHealth intervention development, we conducted a scoping review to map the features and functionality of existing technologies and determine users' perspectives on telerehabilitation and technology for self-management.

METHODS

We followed the Joanna Briggs Institute methodology for scoping reviews. We searched the Embase, Medline, PsycINFO via OVID, and Cochrane Central Register of Controlled Trials databases for manuscripts published from 2001 onward. We included original research articles reporting the use of mobile or computer-based technologies by patients, health care providers, researchers, or family members. Studies were divided into the following 3 categories based on the purpose: validation studies, clinical evaluation, and end user feedback. We extracted general information on study design, technology features, proposed function, and perspectives of health care providers and patients. The protocol for this review is accessible in the Open Science Framework.

RESULTS

Of the 5960 articles, 158 that reported from high-income settings contributed to the qualitative summary (64 studies on mHealth or telerehabilitation programs, 28 validation studies, 38 studies describing users' perceptions). The highest numbers of studies were from Europe or the United Kingdom and North America regarding the use of a mobile app with or without wearables and reported mainly in the last decade. No studies were from low and middle-income settings. The primary functions of technology for remote rehabilitation were education to aid recovery and enable regular, appropriate exercises; monitoring progress of pain (n=19), activity (n=20), and exercise adherence (n=30); 1 or 2-way communication with health care professionals to facilitate the continuum of care (n=51); and goal setting (n=23). Assessment of range of motion (n=16) and gait analysis (n=10) were the commonly validated technologies developed to incorporate into a future rehabilitation program. Few studies (n=14) reported end user involvement during the development stage. We summarized the reasons for satisfaction and dissatisfaction among users across various technologies.

CONCLUSIONS

Several existing mobile and computer-based technologies facilitate post-knee replacement rehabilitation care for patients and health care providers. However, they are limited to high-income settings and may not be extrapolated to low-income settings. A systematic needs assessment of patients undergoing knee replacement and health care providers involved in rehabilitation, involving end users at all stages of development and evaluation, with clear reporting of the development and clinical evaluation can make post-knee replacement rehabilitation care in resource-poor settings accessible and cost-effective.

Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review

In recent years, marked progress has been made in wearable technology for human motion and posture recognition in the areas of assisted training, medical health, VR/AR, etc. This paper systematically reviews the status quo of wearable sensing systems for human motion capture and posture recognition from three aspects, which are monitoring indicators, sensors, and system design. In particular, it summarizes the monitoring indicators closely related to human posture changes, such as trunk, joints, and limbs, and analyzes in detail the types, numbers, locations, installation methods, and advantages and disadvantages of sensors in different monitoring systems. Finally, it is concluded that future research in this area will emphasize monitoring accuracy, data security, wearing comfort, and durability. This review provides a reference for the future development of wearable sensing systems for human motion capture.

Assessment of human gait after total knee arthroplasty by dynamic time warping algorithm

Today, the elderly population is increasing, and there are many drawbacks for them, especially defects in their knee joints which lead to improper gait. To solve this problem, their knee joint can be replaced with knee arthroplasty. In this letter, level of improvement in the human gait before and after total knee arthroplasty (TKA) surgery is investigated using the dynamic time warping (DTW) algorithm. For this purpose, several volunteers who have problems with their knees are incorporated in a test before and after TKA surgery. Then, the data of gait analysis is collected and the data is compared with a reference using the DTW algorithm. The outcome results illustrate an improvement of 89%-97% by the proposed algorithm after TKA surgery. Therefore, patients can see improvement with high accuracy and very fast that result in more use this technique in TKR surgery.

Wide Range Strain Distributions on the Electrode for Highly Sensitive Flexible Tactile Sensor with Low Hysteresis

Flexible piezoresistive tactile sensors are widely used in wearable electronic devices because of their ability to detect mechanical stimuli. However, achieving high sensitivity and low hysteresis over a broad detection range remains a challenge with current piezoresistive tactile sensors. To address these obstacles, we designed elastomeric micropyramid arrays with different heights to redistribute the strain on the electrode. Furthermore, we mixed single-walled carbon nanotubes in the elastomeric micropyramids to compensate for the conductivity loss caused by random cracks in the gold film and increase the adhesion strength between the gold film (deposited on the pyramid surface) and the elastomer. Thus, the energy loss of the sensor during deformation and hysteresis (∼2.52%) was effectively reduced. Therefore, under the synactic effects of the percolation effect, tunnel effect, and multistage strain distribution, the as-prepared sensor exhibited a high sensitivity (1.28 × 10⁶ kPa^-1) and a broad detection range (4.51-54837.06 Pa). The sensitivity was considerably higher than those of most flexible pressure sensors with a microstructure design. As a proof of concept, the sensors were successfully applied in the fields of health monitoring and human-machine interaction.

Telemedicine in orthopaedics and trauma surgery during the first year of COVID pandemic: a systematic review

PURPOSE

Prior to the COVID-19 pandemic, telemedicine in orthopaedics and trauma surgery had mostly developed for joint arthroplasty, fracture management, and general pre- and postoperative care including teleradiology. With the corona-outbreak, telemedicine was applied on a broad scale to prevent assemblage and to guarantee access to medical care protecting critical areas. The purpose of the present study was to give an overview of the spectrum of clinical applications and the efficacy of telemedicine in orthopaedic and trauma surgery as published in times of the COVID-19 pandemic.

METHODS

All published studies investigating the application of telemedicine related to orthopaedics and trauma during the COVID-19 pandemic were accessed and screened for suitability. The primary outcome of interest was the efficacy of telemedicine in various clinical applications. The secondary outcome of interest was the spectrum of different applications in which telemedicine applications were investigated.

RESULTS

The literature search resulted in 1047 articles. After the removal of duplicates, 894 articles were screened of which 31 finally met the inclusion criteria. Dimensions that were described by studies in the literature to have positive effects were preoperative patient optimisation, the usefulness of telemedicine to correctly diagnose a condition, conservative treatment, willingness to and feasibility for telemedicine in patients and doctors, and postoperative/post-trauma care improvement. The efficacy of telemedicine applications or interventions thereby strongly varied and seemed to depend on the exact study design and the research question addressed.

CONCLUSION

Various successful applications of telemedicine have already been reported in orthopaedics and trauma surgery, with a strong increase in scientific output during the COVID-19 years 2020-2021. Whether the advantages of such an approach will lead to a relevant implementation of telemedicine in everyday clinical practice should be monitored after the COVID-19 pandemic.

A Portable Wearable Inertial System for Rehabilitation Monitoring and Evaluation of Patients With Total Knee Replacement

Knee osteoarthritis is a degenerative disease, which greatly affects the daily life of patients. Total knee replacement (TKR) is the most common method to treat knee joint disorders and relieve knee pain. Postoperative rehabilitation exercise is the key to restore knee joint function. However, there is a lack of a portable equipment for monitoring knee joint activity and a systematic assessment scheme. We have developed a portable rehabilitation monitoring and evaluation system based on the wearable inertial unit to estimate the knee range of motion (ROM). Ten TKR patients and ten healthy adults are recruited for the experiment, then the system performance is verified by professional rehabilitation equipment Baltimore Therapeutic Equipment (BTE) Primus RS. The average absolute difference between the knee ROM and BTE Primus RS of healthy subjects and patients ranges from 0.16° to 4.94°. In addition, the knee ROM of flexion-extension and gait activity between healthy subjects and patients showed significant differences. The proposed system is reliable and effective in monitoring and evaluating the rehabilitation progress of patients. The system proposed in this work is expected to be used for long-term effective supervision of patients in clinical and dwelling environments.

A Systematic Review of Diagnostic Accuracy and Clinical Applications of Wearable Movement Sensors for Knee Joint Rehabilitation

In clinical practice, only a few reliable measurement instruments are available for monitoring knee joint rehabilitation. Advances to replace motion capturing with sensor data measurement have been made in the last years. Thus, a systematic review of the literature was performed, focusing on the implementation, diagnostic accuracy, and facilitators and barriers of integrating wearable sensor technology in clinical practices based on a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. For critical appraisal, the COSMIN Risk of Bias tool for reliability and measurement of error was used. PUBMED, Prospero, Cochrane database, and EMBASE were searched for eligible studies. Six studies reporting reliability aspects in using wearable sensor technology at any point after knee surgery in humans were included. All studies reported excellent results with high reliability coefficients, high limits of agreement, or a few detectable errors. They used different or partly inappropriate methods for estimating reliability or missed reporting essential information. Therefore, a moderate risk of bias must be considered. Further quality criterion studies in clinical settings are needed to synthesize the evidence for providing transparent recommendations for the clinical use of wearable movement sensors in knee joint rehabilitation.

A Smartwatch Paired With A Mobile Application Provides Postoperative Self-Directed Rehabilitation Without Compromising Total Knee Arthroplasty Outcomes: A Randomized Controlled Trial

BACKGROUND

Self-directed rehabilitation (SDR) after total knee arthroplasty (TKA) has not been traditionally recommended. The purpose of this study was to determine if there was an impact on postoperative outcomes with the use of an SDR program after primary TKA.

METHODS

In this prospective, randomized, multicenter, controlled trial, we paired a smartwatch with a mobile application, providing an SDR program after TKA. Three groups were examined in this level I study: (1) control group (formal physical therapy [PT]), (2) high exercise compliance group, and (3) low exercise compliance group. Patient-reported outcome measures (PROMs) of knee injury and osteoarthritis outcome scores, joint replacement (KOOS, JR), and EuroQol five-dimension five-level (EQ-5D-5L) along with range of motion (ROM) and manipulation rates were evaluated.

RESULTS

Three hundred thirty-seven patients were enrolled in two groups with 184 in the control group and 153 in the study groups (90 in the high-compliance group and 63 in the low-compliance group). The KOOS, JR score was statistically lower in the low-compliance group in net change from preoperative scores at 3 months (P = .046) and 6 months (P = .032) than that in the control group; difference was noted at 6 months for the high-compliance group, P = .036. However, these did not meet the threshold of 8.02 units for KOOS JR minimal clinically important difference. No differences were seen in PROMs at other time intervals and in manipulation rates or ROM.

CONCLUSION

Postoperative outcomes including manipulation under anesthesia, ROM, and PROMs were not different when a smartwatch paired with a self-directed PT mobile application was compared with traditional formal PT. Surgeons can consider this an appropriate alternative to traditional PT programs after TKA.

Vision-based human joint angular velocity estimation during squat and walking on a treadmill actions

Elderly health monitoring, rehabilitation training, and sport supervision could benefit from continuous assessment of joint angle, and angular velocity to identify the joint movement patterns. However, most of the measurement systems are designed based on special kinematic sensors to estimate angular velocities. The study aims to measure the lower limb joint angular velocity based on a 2D vision camera system during squat and walking on treadmill action using deep convolution neural network (CNN) architecture. Experiments were conducted on 12 healthy adults, and six digital cameras were used to capture the videos of the participant actions in lateral and frontal view. The normalized cross-correlation (Cc_norm) analysis was performed to obtain a degree of symmetry of the ground truth and estimated angular velocity waveform patterns. Mean Cc_norm for angular velocity estimation by deep CNN model has higher than 0.90 in walking on the treadmill and 0.89 in squat action. Furthermore, joint-wise angular velocities at the hip, knee, and ankle joints were observed and compared. The proposed system gets higher estimation performance under the lateral view and the frontal view of the camera. This study potentially eliminates the requirement of wearable sensors and proves the applicability of using video-based system to measure joint angular velocities during squat and walking on a treadmill actions.

Wearable inertial sensors for human movement analysis: a five-year update

INTRODUCTION

The aim of the present review is to track the evolution of wearable IMUs from their use in supervised laboratory- and ambulatory-based settings to their application for long-term monitoring of human movement in unsupervised naturalistic settings.

AREAS COVERED

Four main emerging areas of application were identified and synthesized, namely, mobile health solutions (specifically, for the assessment of frailty, risk of falls, chronic neurological diseases, and for the monitoring and promotion of active living), occupational ergonomics, rehabilitation and telerehabilitation, and cognitive assessment. Findings from recent scientific literature in each of these areas was synthesized from an applied and/or clinical perspective with the purpose of providing clinical researchers and practitioners with practical guidance on contemporary uses of inertial sensors in applied clinical settings.

EXPERT OPINION

IMU-based wearable devices have undergone a rapid transition from use in laboratory-based clinical practice to unsupervised, applied settings. Successful use of wearable inertial sensing for assessing mobility, motor performance and movement disorders in applied settings will rely also on machine learning algorithms for managing the vast amounts of data generated by these sensors for extracting information that is both clinically relevant and interpretable by practitioners.

Inertial measurement units and application for remote healthcare in hip and knee osteoarthritis: a narrative review (Preprint)

Background

Measuring and modifying movement-related joint loading is integral to the management of lower extremity osteoarthritis (OA). Although traditional approaches rely on measurements made within the laboratory or clinical environments, inertial sensors provide an opportunity to quantify these outcomes in patients’ natural environments, providing greater ecological validity and opportunities to develop large data sets of movement data for the development of OA interventions.

Objective

This narrative review aimed to discuss and summarize recent developments in the use of inertial sensors for assessing movement during daily activities in individuals with hip and knee OA and to identify how this may translate to improved remote health care for this population.

Methods

A literature search was performed in November 2018 and repeated in July 2019 and March 2021 using the PubMed and Embase databases for publications on inertial sensors in hip and knee OA published in English within the previous 5 years. The search terms encompassed both OA and wearable sensors. Duplicate studies, systematic reviews, conference abstracts, and study protocols were also excluded. One reviewer screened the search result titles by removing irrelevant studies, and 2 reviewers screened study abstracts to identify studies using inertial sensors as the main sensing technology and a primary outcome related to movement quality. In addition, after the March 2021 search, 2 reviewers rescreened all previously included studies to confirm their relevance to this review.

Results

From the search process, 43 studies were determined to be relevant and subsequently included in this review. Inertial sensors have been successfully implemented for assessing the presence and severity of OA (n=11), assessing disease progression risk and providing feedback for gait retraining (n=7), and remotely monitoring intervention outcomes and identifying potential responders and nonresponders to interventions (n=14). In addition, studies have validated the use of inertial sensors for these applications (n=8) and analyzed the optimal sensor placement combinations and data input analysis for measuring different metrics of interest (n=3). These studies show promise for remote health care monitoring and intervention delivery in hip and knee OA, but many studies have focused on walking rather than a range of activities of daily living and have been performed in small samples (<100 participants) and in a laboratory rather than in a real-world environment.

Conclusions

Inertial sensors show promise for remote monitoring, risk assessment, and intervention delivery in individuals with hip and knee OA. Future opportunities remain to validate these sensors in real-world settings across a range of activities of daily living and to optimize sensor placement and data analysis approaches.

Design of an FPGA-Based Fuzzy Feedback Controller for Closed-Loop FES in Knee Joint Model

Functional electrical stimulation (FES) device has been widely used by spinal cord injury (SCI) patients in their rehab exercises to restore motor function to their paralysed muscles. The major challenge of muscle contraction induced by FES is early muscle fatigue due to the open-loop stimulation strategy. To reduce the early muscle fatigue phenomenon, a closed-loop FES system is proposed to track the angle of the limb’s movement and provide an accurate amount of charge according to the desired reference angle. Among the existing feedback controllers, fuzzy logic controller (FLC) has been found to exhibit good control performance in handling complex non-linear systems without developing any complex mathematical model. Recently, there has been considerable interest in the implementation of FLC in hardware embedded systems. Therefore, in this paper, a digital fuzzy feedback controller (FFC) embedded in a field-programmable gate array (FPGA) board was proposed. The digital FFC mainly consists of an analog-to-digital converter (ADC) Data Acquisition and FLC sub-modules. The FFC was designed to monitor and control the progress of knee extension movement by regulating the stimulus pulse width duration to meet the target angle. The knee is expected to extend to a maximum reference angle setting (70°, 40° or 30°) from its normal position of 0° once the stimulus charge is applied to the muscle by the FES device. Initially, the FLC was modelled using MATLAB Simulink. Then, the FLC was hardcoded into digital logic using hardware description language (HDL) Verilog codes. Thereafter, the performance of the digital FLC was tested with a knee extension model using the HDL co-simulation technique in MATLAB Simulink. Finally, for real-time verification, the designed digital FFC was downloaded to the Intel FPGA (DE2-115) board. The digital FFC utilized only 4% of the total FPGA (Cyclone IV E) logic elements (LEs) and required 238 µs to regulate stimulus pulse width data, including 3 µs for the FLC computation. The high processing speed of the digital FFC enables the stimulus pulse width duration to be updated every stimulation cycle. Furthermore, the implemented digital FFC has demonstrated good control performance in accurately controlling the stimulus pulse width duration to reach the desired reference angle with very small overshoot (1.4°) and steady-state error (0.4°). These promising results are very useful for a real-world closed-loop FES application.

Using Artificial Intelligence for Pattern Recognition in a Sports Context

Optimizing athlete’s performance is one of the most important and challenging aspects of coaching. Physiological and positional data, often acquired using wearable devices, have been useful to identify patterns, thus leading to a better understanding of the game and, consequently, providing the opportunity to improve the athletic performance. Even though there is a panoply of research in pattern recognition, there is a gap when it comes to non-controlled environments, as during sports training and competition. This research paper combines the use of physiological and positional data as sequential features of different artificial intelligence approaches for action recognition in a real match context, adopting futsal as its case study. The traditional artificial neural networks (ANN) is compared with a deep learning method, Long Short-Term Memory Network, and also with the Dynamic Bayesian Mixture Model, which is an ensemble classification method. The methods were used to process all data sequences, which allowed to determine, based on the balance between precision and recall, that Dynamic Bayesian Mixture Model presents a superior performance, with an F1 score of 80.54% against the 33.31% achieved by the Long Short-Term Memory Network and 14.74% achieved by ANN.