Assessment of the Impact of Training Using the Luna-EMG Rehabilitation Robot on the Functional Status of Patients After Total Hip Replacement: A Randomized Trial
Department of Internal Diseases, Rehabilitation and Physical Medicine, Medical University of Lodz, 90-647 Lodz, Poland
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(20), 11065; https://doi.org/10.3390/app152011065
Submission received: 4 July 2025
/
Revised: 3 October 2025
/
Accepted: 14 October 2025
/
Published: 15 October 2025
(This article belongs to the Special Issue Advanced Physical Therapy for Rehabilitation)
Abstract
Background: Total hip replacement is one of the most commonly performed orthopedic procedures in the world. Both before and after the procedure, it is recommended to conduct individually tailored rehabilitation. The recent technological advancements in the field of rehabilitation allow for the use of modern robots in the process of improving patients’ mobility. The main aim of this work is to assess the usefulness of therapy using the Luna-EMG rehabilitation robot in the treatment of patients after total hip arthroplasty. It was checked whether training with this device has a more beneficial effect on the endurance of the lower limb muscles and the overall quality of life of patients than traditional kinesitherapy methods. Materials and methods: The study included 66 patients after total hip arthroplasty. The control group underwent a standard rehabilitation program after arthroplasty procedure, while the experimental group followed the training with the Luna-EMG robot. The effectiveness of the therapy was assessed based on the measurement of the maximum quadriceps muscle tension, as well as its maximum and average strength and the DCFC quality of life rating scale. Results: The study did not find significant differences between the groups regarding the surface tension of the quadriceps muscle (p = 0.1016). The values of maximum and average strength increased in both groups (p = 0.0016). A significant improvement in quality of life was observed in both groups, with a noticeably greater effect recorded in the experimental group (<0.0001). Conclusions: The therapy using Luna-EMG did not have a significant impact on the change in tension and strength of the quadriceps muscle; in terms of muscle strength, it did not show greater effectiveness than traditional kinesitherapy methods. In both groups, there was an improvement in subjective quality of life after rehabilitation, while the effect was greater after therapy with the robot Luna-EMG. This device can increase the attractiveness of physiotherapy conducted in clinical settings, tailor it to the individual preferences of patients, mainly with orthopedic and neurological issues, and thereby enhance motivation and satisfaction with therapy.
1. Introduction
Hip osteoarthritis disease, alongside degenerative changes in the knee joint, is one of the leading causes of activity limitations in the adult population. It is estimated that 240 million people worldwide struggle with this condition [1,2]. Progressive damage to the articular cartilage causes significant pain, stiffness, and a reduced range of motion in the affected joint. This leads to a considerable decline in independence in daily life and the necessity of more frequent use of healthcare services [3].
Guidelines for managing hip osteoarthritis vary depending on the degree of degenerative changes. In the later stages of the disease, performing arthroplasty is recommended [1]. Both before and after the operation, it is recommended to carry out individually tailored physiotherapy aimed at the patient’s return to optimal efficiency [3,4].
A holistic rehabilitation program primarily involves functional exercises focused on rebuilding the strength of the muscles surrounding the hip joint—particularly the quadriceps muscle in the phases of rehabilitation, proprioception training and gait pattern reeducation [4,5,6,7]. An additional aspect influencing the success of therapy is the level of cognitive functioning of the patient, which training should also be considered when planning a comprehensive rehabilitation process [8,9].
Thanks to the rapid technological progress observed in recent years in medicine, many of the aforementioned assumptions can be realized using various types of rehabilitation robots. An example of this solution is the diagnostic-rehabilitation robot Luna-EMG, which engages the patient on various levels, both physically and cognitively, thanks to the biofeedback element. The device allows for objective and precise control of the executed movement as well as systematic monitoring of training progress. Additionally, it is equipped with EMG technology for measuring muscle activity during training or for diagnostic purposes [10,11].
The Luna-EMG device has been designed to support the rehabilitation mainly of neurological patients; however, the manufacturer recommends its use also in orthopedic cases. In addition, the literature presents an increasing number of its alternative applications due to the wide range of capabilities of the machine [11,12,13].
However, there are still few studies focusing on the use of the Luna-EMG robot in rehabilitation following procedures involving the hip joints, which are among the most commonly performed orthopedic surgeries worldwide [14,15]. Most of the research conducted so far has focused on assessing the patients’ condition, overlooking the aspect of the quality of their daily life. The main aim of this pilot study was to assess the impact of training using the Luna-EMG rehabilitation robot on the holistically understood functional state of patients after hip arthroplasty. Training with this robot may have a more beneficial impact on the endurance of lower limb muscles and the subjective quality of life of patients compared to traditional methods of kinesitherapy. Significantly better outcomes of the robot in this regard compared to traditional training are attributed to the element of biofeedback in the form of various available rehabilitation games. Confirmation of this hypothesis will enable a more widespread use of this tool for the rapid re-education of muscle strength after lower limb surgeries.
2. Materials and Methods
2.1. Ethics Statement
The study received a positive opinion from the Bioethics Committee at the Medical University of Lodz No. RNN/128/23/KE, dated 16 May 2023. It was conducted as part of the institution’s statutory activities, and each participant in the study provided informed consent. At every stage, the patient had the right to withdraw from the study without any consequences and with full access to continued treatment.
2.2. Characteristics of Study Participants
Between June 2023 and December 2024, the study included 66 patients (42 women and 24 men) who were hospitalized at the Department of Orthopedic and Post-Traumatic Rehabilitation of the University Clinical Hospital No. 2 in Lodz. The average age of participants was 71.3 ± 8.5, with half of the patients being no older than 71.5 (Q25–Q75: 68–76 years old). The mean time since the surgery was 7.2 ± 11.5 months, with half of the participants having undergone the procedure no more than 4 months prior (Q25–Q75: 2–6 months).
2.3. Eligibility Criteria
The inclusion criterion was a condition following an uncomplicated total hip replacement due to advanced osteoarthritis and the patient’s consent to participate in the training procedure. On the other hand, the exclusion criteria included age over 90 years, complicated course of surgical treatment (thromboembolic disease, perioperative infections and a history of prosthesis dislocation), the use of rehabilitation involving other robotic rehabilitation devices within the six months preceding admission to the clinic and refusal to participate in the study.
2.4. Study Design
In the control group, postoperative rehabilitation was conducted in accordance with the latest guidelines [14,15], without the use of modern technologies. The rehabilitation protocol was based on isometric exercises of the quadriceps and gluteal muscles in different positions, proprioception training, and exercises on the lower limb rotor exercises. In contrast, the study group underwent therapy using a rehabilitation system composed of the Luna-EMG robot and the MezosSIT chair, both developed by EGZOTech (Gliwice, Poland). The exercise protocol for this group consisted of an intensive 30 min training session with the Luna-EMG, allocating 15 min per limb, utilizing the following manufacturer-recommended programs: dynamic continuous responsiveness, visible or hidden proprioception, and the orthopedic game. Each program lasted 5 min, and the level of difficulty and load was individually adjusted to the patients’ functional and cognitive abilities. The protocol was supplemented with isometric exercises for the gluteal muscles and lower limb rotor exercises. The therapy was conducted daily during a three-week hospitalization period, with a weekend break.
For the purposes of the study, a specially designed questionnaire was prepared, which was administered before the therapy began and after it was completed. The Luna-EMG robot was also used as a diagnostic tool. It was employed to measure the maximum surface tension as well as the maximum and average strength of the quadriceps muscle in both limbs, with all measurements performed according to the manufacturer’s recommendations. To increase objectivity, muscle strength was also tested using the MicroFET 2 dynamometer (Hoggan Scientific, Salt Lake City, UT, USA). The examination was always conducted by the same physiotherapist to eliminate potential measurement errors.
Additionally, the questionnaire included, besides basic demographic data, the scale for assessing quality of life DCFC (Dartmouth Coop Function Charts) to provide a comprehensive overview of the participants’ functional status. This point scale was used to assess the overall health status of the patient over the past four weeks. It consists of nine subcategories: physical condition, emotional feelings, daily activities, social activities, pain, changes in health, overall health status, social support and quality of life. Three numerical ranges were used for its interpretation, with scores of 35–45 indicating poor quality of life, 22–34 average, and 9–21 good [16].
The design of this two-arm trial involved a random and blind division of participants into two groups; researchers had no influence on the assignment of individual patients to groups after conducting the initial study based on the designed questionnaire. A completely randomized allocation procedure was decided upon to eliminate selection bias in group assignment as much as possible.
2.5. Statistical Methods
Quantitative variables were described by providing the mean and standard deviation (SD), ordinal measures: median (Me) and quartiles (Q25 and Q75), as well as minimum and maximum (Min-Max). The normality of the variables was verified using the Shapiro–Wilk normality test. For categorical variables, the number of observations with a given category and the corresponding percentage were provided. A Student’s t-test was used to compare two independent groups (in the case of normal distribution in the compared groups) or the non-parametric Mann–Whitney U test (in the absence of normality). For qualitative variables, the chi-squared test of independence was used to compare the groups.
To compare groups considering repeated measurements due to unmet assumptions (normality of the distribution of the studied variables, equality of variances, sphericity), a two-way analysis of variance in its non-parametric version—the so-called ART ANOVA (Aligned Ranks Transformation ANOVA) was used. For post hoc comparisons, Tukey’s test was applied with Bonferroni correction.
For comparisons before and after therapy within each group, the effect size was additionally calculated using Cohen’s d measure. The effect size is considered small when d ∈ [0.2–0.5), medium when d ∈ [0.5–0.8), and large when d ≥ 0.8. Results with p < 0.05 were considered statistically significant. Statistical analyses were performed using the PQStat software version 1.8.6 and the ARTool package.
3. Results
The experimental group consisted of 34 individuals (51.5%), while the control group comprised 32 individuals (48.5%). A comparative characterization of both groups is presented in Table 1. The groups did not differ significantly in terms of age, gender, BMI, time since the procedure, type of prosthesis, and orthopedic supply. The average age in the study group was 71.3 ± 8.2 years, and in the control group it was 71.3 ± 9.0 years. In both groups, a predominance of women was noted (25; 73.5% in the study group and 17; 53.1% in the control group), what is perceived as a limitation of the study. The average body mass index in the study group was 28.3 ± 4.5 kg/m2, while in the control group it was 27.7 ± 5.0 kg/m2. The average body mass index in the study group was 28.3 ± 4.5 kg/m2, while in the control group it was 27.7 ± 5.0 kg/m2. The average time since surgery in the study group was 6.9 ± 12 months, and in the control group—7.5 ± 11.1 months; in half of the patients in each group, this time did not exceed 4 months. In both groups, there was a clear dominance of individuals with uncemented prostheses (around 94% of patients). In both the study and control groups, the majority of individuals did not require orthopedic supplies (50% and 46.9% of patients, respectively).
The study compared the maximum surface tension of the quadriceps muscle of the operated and unaffected limb measured using the Luna-EMG robot before and after therapy in both examined groups (Table 2). No statistically significant differences were found between the groups for either the operated or the unaffected limb, before and after therapy. No significant changes were also observed within each group before and after therapy for both limbs.
Table 3 presents the results of the comparison of the maximum strength of the quadriceps muscle in the operated and unaffected limbs, measured using the Luna-EMG robot, before and after therapy in the groups under study.
In the case of the operated limb, no statistically significant differences were found between the groups, either before or after therapy. In the study group after therapy, a statistically significant increase in the maximum strength of the quadriceps muscle was observed. The maximum strength before therapy was on average 20.35 ± 11.73 and after therapy it increased to 27.37 ± 12.45 (p = 0.0016). The obtained effect should be considered large. For the control group, an increase in maximum strength was also observed after therapy, but this change was not statistically significant (p = 0.1391).
However in the case of the unaffected limb, no statistically significant differences were found between the groups, either before or after therapy. However, within each group, a statistically significant increase in the maximum strength of the quadriceps muscle was observed after therapy. For the study group, the maximum strength before therapy was an average of 24.1 ± 14.99, and after therapy, it increased to 33.2 ± 21.54 (p = 0.0056). For the control group, the maximum strength before therapy was an average of 24.49 ± 16.49, and after therapy, it increased to 31.03 ± 17.58 (p = 0.0182). In both cases, the effect size should be considered large.
In the case of the operated limb, no statistically significant differences were found between the groups, either before or after therapy (Table 4). In the studied group, a statistically significant increase in the average strength of the quadriceps muscle was observed after therapy. The average strength before therapy was 6.99 ± 4.02, and after therapy it increased to 10.05 ± 5.57 (p = 0.0016). The effect size should be considered large. In the control group, an increase in average strength after therapy was also observed, but this change was not statistically significant (p = 0.0706).
Regarding the average strength of the quadriceps muscle in the unaffected limb, no statistically significant differences were found between the groups, either before or after therapy. No significant changes were observed within each group before and after therapy, and the observed increase in values after therapy was not statistically significant (Table 4).
To verify the measurement reliability of the Luna-EMG robot, an additional method of measuring quadriceps muscle strength was decided upon using a traditional dynamometer. Table 5 shows the results of the comparison of quadriceps muscle strength in the operated and unaffected limb measured using MicroFET dynamometer before and after therapy in the compared groups.
In the case of the operated limb, no statistically significant differences were observed between the groups, either before or after therapy. In the study group, a statistically significant increase in quadriceps muscle strength was observed after therapy. The muscle strength before therapy was on average 150.18 ± 58.67, and after therapy it increased to 183.48 ± 72.09 (p = 0.0002). For the control group, a statistically significant (p = 0.0025) in-crease in quadriceps muscle strength after therapy was also observed—from 150.55 ± 54.31 to 178.9 ± 60.35, respectively. In both cases, the effect size obtained should be considered large (with a slightly smaller effect observed in the control group).
For the unaffected limb, no statistically significant differences were found between the groups, both before and after therapy. In the studied group, a statistically significant increase in quadriceps muscle strength was observed after therapy. The muscle strength before therapy was on average 172.1 ± 52.13, and after therapy it increased to 207.66 ± 76.33 (p = 0.0009). The effect size should be considered large. In the control group, muscle strength also increased after therapy, but this change was not statistically significant (p = 0.0589).
To provide a more comprehensive picture of the patients’ functional status, the study included the DCFC quality of life scale, which was compared between both groups before and after hospitalization (Table 6).
No statistically significant differences were found between the groups in terms of quality of life according to the DCFC scale before therapy. However, a statistically significant difference (p < 0.0001), between the groups was observed after therapy (the average score in the study group after therapy was 14.71 ± 4.16 points and in the control group 23.81 ± 5.62 points). A statistically significant improvement in quality of life, measured by the number of points on the DCFC scale, was observed within each group.
In the studied group before therapy, the average score on the DCFC scale was 24.91 ± 5.12 and decreased to 14.71 ± 4.16 points after therapy (p < 0.0001). In the control group, before therapy, the average score on the DCFC scale was 27.81 ± 6.68 and decreased to 23.81 ± 5.62 points after therapy (p = 0.0001). In both cases, the effect size was large, with the study group showing an effect nearly twice as large as that observed in the control group.
4. Discussion
In recent years, trends towards the automation and robotization of many procedures in medicine can be observed. In rehabilitation, such actions enable greater personalization of the algorithms applied in various diseases and objective monitoring of therapy effects in real time [17,18]. Additionally, the COVID-19 pandemic forced the search for innovative solutions in the field of physiotherapy without the need for direct contact with the patient, which led to an increased use of rehabilitation robots in everyday clinical practice [12,19,20,21,22,23,24].
After hip joint arthroplasty, a key element of rehabilitation is muscle strengthening, including the quadriceps femoris muscle. Its performance, on both the operated and non-operated sides, was assessed based on the values of maximum surface tension as well as maximum and average contraction strength. It was decided to take measurements of both limbs to check the effectiveness of both therapeutic interventions on the muscle structures operating under physiological conditions. In the case of quadriceps muscle tension in both limbs, no statistically significant differences were observed either before and after therapy or between the study groups. Many researchers have obtained opposite results, indicating the high effectiveness of training with the Luna-EMG robot in altering surface muscle tension or have used it as a diagnostic parameter [23,25,26,27]. However, it should be emphasized that none of these studies focused on rehabilitation after orthopedic surgeries, which may affect the observed differences.
In contrast, the analysis of measurements of maximum and average quadriceps muscle strength in both limbs showed an increase in these parameters in both the experimental and control groups. However, no statistically significant difference was proven between the two groups, which does not allow for a definitive conclusion regarding the superiority of robot-assisted training over traditional kinesiotherapy. Although numerous reports have been found in the literature regarding the positive impact of this type of training on muscle strength increase in various conditions [23,25]. This may indicate the low effectiveness of training with the Luna-EMG robot in this particular group of patients.
The use of results from a traditional dynamometer for measuring muscle strength provides a basis for stating that the Luna-EMG can serve as an objective and reliable diagnostic tool for assessing muscle strength, given the recorded increase in this parameter on both devices. This is supported by findings in the literature [11,22]. However, due to differences in measurement units, it is not possible to accurately compare the obtained values—only the direction of parameter changes can be evaluated. To assess the agreement between the measurements of muscle strength using a traditional dynamometer and Luna-EMG robot, the Pearson’s correlation coefficient (R) and the intraclass correlation coefficient (ICC) were calculated after making the measurement results comparable through standardization. The values of ICC show fair to good agreement, respectively, for the average strength of the quadriceps muscle of the unaffected limb before therapy: R = 0.3314; p = 0.007; ICC = 0.5016; for the average strength of the quadriceps muscle of the unaffected limb after therapy: R = 0.2984; p = 0.015; ICC = 0.4635; for the average strength of the quadriceps muscle of the operated limb before therapy: R = 0.3160; p = 0.010; ICC = 0.4841; for the average strength of the quadriceps muscle of the operated limb after therapy: R = 0.5141; p < 0.001; ICC = 0.6982.
In postoperative patients, a holistic approach to their rehabilitation process is crucial so that they can safely and comfortably function in daily life. That is why the study included not only physical characteristics but also the subjective assessment of their own health status and functioning by the patients. A significantly greater effect was observed in the group undergoing therapy with the Luna-EMG. It can be assumed that rehabilitation involving a modern and cognitively engaging device, as well as the perceived distinction associated with random assignment to the experimental group, contributed to the differences observed between the groups. Many authors have also reported a similar impact of robotic rehabilitation on patients’ quality of life [28,29]. However, the literature is not without opposing reports, with some studies suggesting a small effect of robotic therapy in this aspect of rehabilitation [30,31,32]. This may be due to the situation where patients randomly assigned to training with a robot may have felt supereminent. This is due to the fact that rehabilitation robots in many centers still represent a kind of novelty. This may lead to greater motivation and engagement in training, and consequently an increase in subjective quality of life.
The data collected during the study do not allow for a clear indication of the superiority of robotic rehabilitation over traditional training, which may be an important perspective in the discussion about potentially replacing medical staff with robots in the future. However, several interesting directions for the potential clinical use of the obtained results can be outlined. Despite the lack of a statistically significant difference between the compared therapeutic interventions in terms of muscle strength, the Luna-EMG robot meets the objective of increasing the discussed parameter. Therefore, it can be used as a helpful tool in the reeducation of muscle strength after lower limb surgeries, but with a great deal of caution. This stems from the limitations of the current study, including the relatively small sample size and the lack of a formal calculation of it, the wide range of time that has elapsed since the surgical procedure, and the age and gender disparities between the groups. A significant range in the case of these features could have influenced the shape of the obtained results, for example, on the lack of impact on the surface tension of the quadriceps muscle, which depends on many factors. For this reason, future studies should focus on evaluating resistance training using Luna-EMG in patients in the first weeks after surgery when the muscles are significantly weakened or introduce an age and gender division within the studied groups. The discrepancies between the Polish version of the DCFC scale and its international counterparts are also significant.
Clearly, further research is needed to assess the impact of different training protocols using Luna-EMG on larger and more homogeneous groups of orthopedic patients. The current pilot study is the start of considerations for creating evidence-based protocols to systematize the procedures that fully utilize the capabilities of this machine.
5. Conclusions
Therapy using the Luna-EMG rehabilitation robot does not significantly improve maximum surface muscle tension or the maximum and average strength of the quadriceps femoris muscle better than traditional methods of kinesitherapy in patients after hip joint arthroplasty. However, it has a positive effect on the subjective assessment of quality of life in this patient group. Luna-EMG can be used as a complementary element of rehabilitation programs, as well as an objective diagnostic tool. It can contribute to a significant increase in the attractiveness of clinical physiotherapy and help in selecting exercises according to patients’ preferences. This will have a positive impact on their motivation to take care of their fitness. As a result, the device will be effective during the rehabilitation of orthopedic and neurological patients in the early stages, for whom engaging in rehabilitation-related effort poses a great challenge.
Author Contributions
Conceptualization, A.M. and A.P.; methodology, A.M.; software, A.M.; validation, A.P. and R.I.; formal analysis, A.P.; investigation, A.M.; resources, A.M.; data curation, A.M.; writing—original draft preparation, A.M.; writing—review and editing, A.P.; visualization, A.M.; supervision, R.I.; project administration, A.M.; funding acquisition, R.I. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Bioethics Committee at the Medical University of Lodz No. RNN/128/23/KE, dated 16 May 2023.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.
Conflicts of Interest
The authors declare no conflicts of interest.
References
- Katz, J.N.; Arant, K.R.; Loeser, R.F. Diagnosis and treatment of hip and knee osteoarthritis: A review. JAMA 2021, 325, 568–578. [Google Scholar] [CrossRef]
- Courties, A.; Berenbaum, F. Is hip osteoarthritis preventable? Jt. Bone Spine 2020, 87, 371–375. [Google Scholar] [CrossRef]
- Lespasio, M.J.; Sultan, A.A.; Piuzzi, N.S.; Khlopas, A.; Husni, M.E.; Muschler, G.F.; Mont, M.A. Hip Osteoarthritis: A Primer. Perm. J. 2018, 22, 17-084. [Google Scholar] [CrossRef]
- Colibazzi, V.; Coladonato, A.; Zanazzo, M.; Romanini, E. Evidence based rehabilitation after hip arthroplasty. Hip Int. 2020, 30 (Suppl. S2), 20–29. [Google Scholar] [CrossRef]
- Skou, S.T.; Roos, E.M. Physical therapy for patients with knee and hip osteoarthritis: Supervised, active treatment is current best practice. Clin. Exp. Rheumatol. 2019, 37 (Suppl. S120), 112–117. [Google Scholar]
- Liu, Z.; Chang, J.; Liu, Y.; Ma, Y.; Ding, X.; Huo, J. Efficacy of Bed Exercise Following Primary Total Hip Replacement in Young Active Patients. Med. Sci. Monit. 2025, 31, e946819. [Google Scholar] [CrossRef] [PubMed]
- Nicolau, C.; Mendes, L.; Ciríaco, M.; Ferreira, B.; Baixinho, C.L.; Fonseca, C.; Ferreira, R.; Sousa, L. Educational Intervention in Rehabilitation to Improve Functional Capacity after Hip Arthroplasty: A Scoping Review. J. Pers. Med. 2022, 12, 656. [Google Scholar] [CrossRef] [PubMed]
- Zhang, Q.; Fu, Y.; Lu, Y.; Zhang, Y.; Huang, Q.; Yang, Y.; Zhang, K.; Li, M. Impact of Virtual Reality-Based Therapies on Cognition and Mental Health of Stroke Patients: Systematic Review and Meta-analysis. J. Med. Internet Res. 2021, 23, e31007. [Google Scholar] [CrossRef] [PubMed]
- Ding, K.; Song, F.; Sun, W.; Sun, M.; Xia, R. Impact of exercise training on cognitive function in patients with COPD: A systematic review and meta-analysis of randomised controlled trials. Eur. Respir. Rev. 2025, 34, 240170. [Google Scholar] [CrossRef]
- Peternel, L.; Tsagarakis, N.; Ajoudani, A. A Human-Robot Co-Manipulation Approach Based on Human Sensorimotor Information. IEEE Trans. Neural Syst. Rehabil. Eng. 2017, 25, 811–822. [Google Scholar] [CrossRef]
- Leszczak, J.; Wolan-Nieroda, A.; Drużbicki, M.; Poświata, A.; Mikulski, M.; Roksela, A.; Guzik, A. Evaluation of Reliability of the Luna EMG Rehabilitation Robot to Assess Proprioception in the Upper Limbs in 102 Healthy Young Adults. Med. Sci. Monit. 2024, 30, e942439. [Google Scholar] [CrossRef]
- Trzmiel, T.; Marchewka, R.; Pieczyńska, A.; Zasadzka, E.; Zubrycki, I.; Kozak, D.; Mikulski, M.; Poświata, A.; Tobis, S.; Hojan, K. The Effect of Using a Rehabilitation Robot for Patients with Post-Coronavirus Disease (COVID-19) Fatigue Syndrome. Sensors 2023, 23, 8120. [Google Scholar] [CrossRef]
- Lewandowska-Sroka, P.; Stabrawa, R.; Kozak, D.; Poświata, A.; Łysoń-Uklańska, B.; Bienias, K.; Roksela, A.; Kliś, M.; Mikulski, M. The Influence of EMG-Triggered Robotic Movement on Walking, Muscle Force and Spasticity after an Ischemic Stroke. Medicina 2021, 57, 227. [Google Scholar] [CrossRef]
- Rampazo-Lacativa, M.K.; D’Elboux, M.J. Effect of cycle ergometer and conventional exercises on rehabilitation of older patients with total hip arthroplasty: Study protocol for randomized controlled trial. Trials 2015, 16, 139. [Google Scholar] [CrossRef] [PubMed]
- Austin, M.S.; Urbani, B.T.; Fleischman, A.N.; Fernando, N.D.; Purtill, J.J.; Hozack, W.J.; Parvizi, J.; Rothman, R.H. Formal Physical Therapy After Total Hip Arthroplasty Is Not Required: A Randomized Controlled Trial. J. Bone Jt. Surg. Am. 2017, 99, 648–655. [Google Scholar] [CrossRef] [PubMed]
- Nelson, E.C.; Landgraf, J.M.; Hays, R.D.; Kirk, J.W.; Wasson, J.W.; Keller, A.; Zubkoff, M. Functional Status Measurement in Primary Care; WONCA Classification Committee: New York, NY, USA, 1990; Springer: Berlin/Heidelberg, Germany, 2012. [Google Scholar]
- Chua, K.S.G.; Piravej, K.; Kang, J.H.; Chou, L.W. Editorial for the Special Issue “Physical Medicine and Rehabilitation: Trends and Applications”. Life 2025, 15, 419. [Google Scholar] [CrossRef]
- Mizna, S.; Arora, S.; Saluja, P.; Das, G.; Alanesi, W.A. An analytic research and review of the literature on practice of artificial intelligence in healthcare. Eur. J. Med. Res. 2025, 30, 382. [Google Scholar] [CrossRef] [PubMed]
- Zasadzka, E.; Tobis, S.; Trzmiel, T.; Marchewka, R.; Kozak, D.; Roksela, A.; Pieczyńska, A.; Hojan, K. Application of an EMG-Rehabilitation Robot in Patients with Post-Coronavirus Fatigue Syndrome (COVID-19)-A Feasibility Study. Int. J. Environ. Res. Public Health 2022, 19, 10398. [Google Scholar] [CrossRef]
- Bernhardsson, S.; Larsson, A.; Bergenheim, A.; Ho-Henriksson, C.M.; Ekhammar, A.; Lange, E.; Larsson, M.E.H.; Nordeman, L.; Samsson, K.S.; Bornhöft, L. Digital physiotherapy assessment vs. conventional face-to-face physiotherapy assessment of patients with musculoskeletal disorders: A systematic review. PLoS ONE 2023, 18, e0283013. [Google Scholar] [CrossRef]
- Shim, G.Y.; Kim, E.H.; Baek, Y.J.; Chang, W.K.; Kim, B.R.; Oh, J.H.; Lee, J.I.; Hwang, J.H.; Lim, J.Y. A randomized controlled trial of postoperative rehabilitation using digital healthcare system after rotator cuff repair. NPJ Digit. Med. 2023, 6, 95. [Google Scholar] [CrossRef]
- Areias, A.C.; Costa, F.; Janela, D.; Molinos, M.; Moulder, R.G.; Lains, J.; Scheer, J.K.; Bento, V.; Yanamadala, V.; Correia, F.D. Long-Term Clinical Outcomes of a Remote Digital Musculoskeletal Program: An Ad Hoc Analysis from a Longitudinal Study with a Non-Participant Comparison Group. Healthcare 2022, 10, 2349. [Google Scholar] [CrossRef]
- Zębalski, M.A.; Parysek, K.; Krzywon, A.; Nowosielski, K. LUNA EMG as a Marker of Adherence to Prehabilitation Programs and Its Effect on Postoperative Outcomes among Patients Undergoing Cytoreductive Surgery for Ovarian Cancer and Suspected Ovarian Tumors. Cancers 2024, 16, 2493. [Google Scholar] [CrossRef] [PubMed]
- Leszczak, J.; Pniak, B.; Drużbicki, M.; Poświata, A.; Mikulski, M.; Roksela, A.; Guzik, A. Assessment of inter-rater and intra-rater reliability of the Luna EMG robot as a tool for assessing upper limb proprioception in patients with stroke-a prospective observational study. PeerJ 2024, 12, e17903. [Google Scholar] [CrossRef] [PubMed]
- Korczyński, B.; Frasuńska, J.; Poświata, A.; Siemianowicz, A.; Mikulski, M.; Tarnacka, B. Surface electromyography vs. clinical outcome measures after robot-assisted gait training in patients with spinal cord injury after post-acute phase of rehabilitation. Ann. Agric. Environ. Med. 2024, 31, 599–608. [Google Scholar] [CrossRef]
- Olczak, A.; Truszczyńska-Baszak, A.; Gniadek-Olejniczak, K. The Relationship between the Static and Dynamic Balance of the Body, the Influence of Eyesight and Muscle Tension in the Cervical Spine in CAA Patients—A Pilot Study. Diagnostics 2021, 11, 2036. [Google Scholar] [CrossRef]
- Olczak, A.; Truszczyńska-Baszak, A. Influence of the Passive Stabilization of the Trunk and Upper Limb on Selected Parameters of the Hand Motor Coordination, Grip Strength and Muscle Tension, in Post-Stroke Patients. J. Clin. Med. 2021, 10, 2402. [Google Scholar] [CrossRef]
- Taravati, S.; Capaci, K.; Uzumcugil, H.; Tanigor, G. Evaluation of an upper limb robotic rehabilitation program on motor functions, quality of life, cognition, and emotional status in patients with stroke: A randomized controlled study. Neurol. Sci. 2022, 43, 1177–1188. [Google Scholar] [CrossRef]
- Moghadasi, A.N.; Rastkar, M.; Mohammadifar, M.; Mohammadi, A.; Ghajarzadeh, M. Effects of robotic rehabilitation on fatigue experience, disability, and quality of life in patients with multiple sclerosis (MS): A systematic review and meta-analysis. Caspian J. Intern. Med. 2024, 15, 589–600. [Google Scholar] [CrossRef]
- Adar, S.; Keskin, D.; Dündar, Ü.; Toktaş, H.; Yeşil, H.; Eroğlu, S.; Eyvaz, N.; Beştaş, E.; Demircan, A. Effect of Robotic Rehabilitation on Hand Functions and Quality of Life in Children with Cerebral Palsy: A Prospective Randomized Controlled Study. Am. J. Phys. Med. Rehabil. 2024, 103, 716–723. [Google Scholar] [CrossRef]
- Fareh, R.; Elsabe, A.; Baziyad, M.; Kawser, T.; Brahmi, B.; Rahman, M.H. Will Your Next Therapist Be a Robot?-A Review of the Advancements in Robotic Upper Extremity Rehabilitation. Sensors 2023, 23, 5054. [Google Scholar] [CrossRef]
- Varoqui, D.; Niu, X.; Mirbagheri, M.M. Ankle voluntary movement enhancement following robotic-assisted locomotor training in spinal cord injury. J. Neuroeng. Rehabil. 2014, 11, 46. [Google Scholar] [CrossRef] [PubMed]
Table 1.
Characteristics of the compared groups.
| Variable | Statistical Measures | Group | p-Value | ||
|---|---|---|---|---|---|
| Study Group (n = 34) | Control Group (n = 32) | ||||
| Age | Mean ± SD | 71.3 ± 8.2 | 71.3 ± 9.0 | 0.5673 | |
| Me [Q25; Q75] | 72 [70; 76] | 70.5 [66.8; 77] | |||
| Min; Max | 44; 87 | 52; 90 | |||
| Gender | F | n (%) | 25 (73.5%) | 17 (53.1%) | 0.0850 |
| M | 9 (26.5%) | 15 (46.9%) | |||
| BMI | Mean ± SD | 28.3 ± 4.5 | 27.7 ± 5.0 | 0.5717 | |
| Me [Q25; Q75] | 28.0 [24.6; 32.1] | 26.4 [24.4; 30.5] | |||
| Min; Max | 20.5; 36.1 | 19.3; 37.3 | |||
| BMI | norm | n (%) | 10 (29.4%) | 11 (34.4%) | 0.8122 |
| overweight | 12 (35.3%) | 12 (37.5%) | |||
| obesity | 12 (35.3%) | 9 (28.1%) | |||
| Time (months) | Mean ± SD | 6.9 ± 12 | 7.5 ± 11.1 | 0.6332 | |
| Me [Q25; Q75] | 4 [2; 5.8] | 4 [2; 6.5] | |||
| Min; Max | 0.2; 53 | 0.1; 55 | |||
| Type of endoprosthesis | non-cemented | n (%) | 32 (94.1%) | 30 (93.7%) | 0.6502 |
| cemented | 2 (5.9%) | 2 (6.3%) | |||
| Orthopedic supplies | none | n (%) | 17 (50%) | 15 (46.9%) | 0.1255 |
| 1 crutch | 5 (14.7%) | 4 (12.5%) | |||
| 2 crutches | 10 (29.4%) | 5 (15.6%) | |||
| walking frame | 2 (5.9%) | 8 (25%) | |||
Table 2.
The maximum tension of the quadriceps muscle of the operated and unaffected limb measured using the Luna-EMG robot before and after therapy in the compared groups.
Table 2.
The maximum tension of the quadriceps muscle of the operated and unaffected limb measured using the Luna-EMG robot before and after therapy in the compared groups.
| Group | Measures | Max Tension Operated Limb (µV) | p-Value (Before vs. After Therapy) | Cohen’s d | Max Tension Unaffected Limb (µV) | p-Value (Beforevs. After Therapy) | Cohen’s d | ||
|---|---|---|---|---|---|---|---|---|---|
| Before Therapy | After Therapy | Before Therapy | After Therapy | ||||||
| Study group | Mean ± SD | 183.37 ± 108.72 | 221.95 ± 119.28 | 0.1016 | 0.8567 | 215.59 ± 124.05 | 244.38 ± 112.57 | 0.2777 | 0.5091 |
| Me [Q25; Q75] | 170.13 [103.83; 225.04] | 208.67 [145.38; 261.28] | 178.49 [119.27; 286.53] | 245.72 [159.73; 289.52] | |||||
| Min; Max | 30.96; 510.87 | 36.7; 626.52 | 36.63; 565.42 | 56.25; 577.13 | |||||
| Control group | Mean ± SD | 195.6 ± 112.7 | 226.22 ± 90.89 | 0.0876 | 0.6385 | 198.18 ± 118.1 | 218.24 ± 95.24 | 0.3959 | 0.8867 |
| Me [Q25; Q75] | 186.24 [107.14; 240.93] | 215.81 [182.16; 259.08] | 191.2 [130.13; 237.37] | 227.35 [141.44; 266.91] | |||||
| Min; Max | 60.15; 483.03 | 63.7; 513.8 | 37.35; 656.95 | 62.15; 438.93 | |||||
| p-value (comparison of groups) | 0.9721 | 0.9504 | x | 0.9116 | 0.8601 | x | |||
Table 3.
Maximum strength of the quadriceps muscle of the operated and unaffected limb measured using the Luna-EMG robot before and after therapy in the compared groups.
Table 3.
Maximum strength of the quadriceps muscle of the operated and unaffected limb measured using the Luna-EMG robot before and after therapy in the compared groups.
| Group | Measures | Max Strength Operated Limb (Nm) | p-Value (Before vs. After Therapy) | Cohen’s d | Max Strength Unaffected Limb (Nm) | p-Value (Before vs. After Therapy) | Cohen’s d | ||
|---|---|---|---|---|---|---|---|---|---|
| Before Therapy | After Therapy | Before Therapy | After Therapy | ||||||
| Study group | Mean ± SD | 20.35 ± 11.73 | 27.37 ± 12.45 | 0.0016 | 1.6815 | 24.1 ± 14.99 | 33.2 ± 21.54 | 0.0056 | 1.0572 |
| Me [Q25; Q75] | 18.5 [10.05; 30.53] | 25 [19.13; 34.05] | 21.17 [12.8; 33.25] | 29.3 [23.33; 36.43] | |||||
| Min; Max | 5.7; 42.8 | 8; 63.5 | 6.1; 69.8 | 6.8; 122.96 | |||||
| Control group | Mean ± SD | 23.26 ± 12.86 | 27.81 ± 14.63 | 0.1391 | 0.5632 | 24.49 ± 16.49 | 31.03 ± 17.58 | 0.0182 | 1.0584 |
| Me [Q25; Q75] | 19.7 [13.88; 27.58] | 24.85 [15.98; 37.05] | 18.7 [11.6; 31.24] | 26.95 [17.53; 37.15] | |||||
| Min; Max | 7; 58.7 | 6.4; 63.5 | 7.2; 67.9 | 6.8; 71.9 | |||||
| p-value (comparison of groups) | 0.8544 | 0.9969 | x | 0.9985 | 0.9844 | x | |||
Table 4.
The average strength of the quadriceps muscle of the operated and unaffected limb measured using the Luna-EMG robot before and after therapy in the compared groups.
Table 4.
The average strength of the quadriceps muscle of the operated and unaffected limb measured using the Luna-EMG robot before and after therapy in the compared groups.
| Group | Measures | Average Strength Operated Limb (Nm) | p-Value (Before vs. After Therapy) | Cohen’s d | Average Strength Unaffected Limb (Nm) | p-Value (Before vs. After Therapy) | Cohen’s d | ||
|---|---|---|---|---|---|---|---|---|---|
| Before Therapy | After Therapy | Before Therapy | After Therapy | ||||||
| Study group | Mean ± SD | 6.99 ± 4.02 | 10.05 ± 5.57 | 0.0016 | 1.3385 | 8.96 ± 5.58 | 11.21 ± 6.59 | 0.0697 | 0.6869 |
| Me [Q25; Q75] | 5.05 [3.5; 10] | 9.11 [6.13; 13.1] | 8.25 [4.2; 12.4] | 9.5 [7.08; 12.48] | |||||
| Min; Max | 2.6; 16.7 | 3; 29.5 | 1.3; 23.4 | 2.5; 31.1 | |||||
| Control group | Mean ± SD | 7.76 ± 5.95 | 10 ± 6.53 | 0.0706 | 0.5856 | 8.88 ± 6.96 | 10.48 ± 6.71 | 0.1301 | 0.6693 |
| Me [Q25; Q75] | 5.6 [4.55; 8.13] | 8.5 [5.1; 13.78] | 6.25 [4.38; 10.98] | 8.55 [5.93; 13.53] | |||||
| Min; Max | 1.5; 30.8 | 2; 29.8 | 2.6; 33.4 | 1.7; 31.4 | |||||
| p-value (comparison of groups) | 0.9701 | 0.9714 | x | 0.9681 | 0.9334 | x | |||
Table 5.
The strength of the quadriceps muscle of the operated and unaffected limb measured using MicroFET before and after therapy in the compared groups.
Table 5.
The strength of the quadriceps muscle of the operated and unaffected limb measured using MicroFET before and after therapy in the compared groups.
| Group | Measures | Strength MicroFET Operated Limb (µN) | p-Value (Before vs. After Therapy) | Cohen’s d | Strength MicroFET Unaffected Limb (µN) | p-Value (Before vs. After Therapy) | Cohen’s d | ||
|---|---|---|---|---|---|---|---|---|---|
| Before Therapy | After Therapy | Before Therapy | After Therapy | ||||||
| Study group | Mean ± SD | 150.18 ± 58.67 | 183.48 ± 72.09 | 0.0002 | 1.9208 | 172.1 ± 52.13 | 207.66 ± 76.33 | 0.0009 | 1.9406 |
| Me [Q25; Q75] | 135.85 [115.43; 172.13] | 176.25 [126.33; 231.65] | 163.45 [138.95; 209.15] | 207.3 [156.1; 234.98] | |||||
| Min; Max | 39.1; 329.6 | 67.6; 353.7 | 84.1; 292 | 95.1; 424 | |||||
| Control group | Mean ± SD | 150.55 ± 54.31 | 178.9 ± 60.35 | 0.0025 | 1.6283 | 168.6 ± 57.87 | 192.85 ± 63.05 | 0.0589 | 1.2464 |
| Me [Q25; Q75] | 160.55 [115.95; 180.7] | 174.8 [149.48; 213.3] | 178.35 [119.95; 213.5] | 183.15 [149.98; 244.2] | |||||
| Min; Max | 15.5; 260.2 | 24.3; 302.9 | 41.3; 270.9 | 56; 338.1 | |||||
| p-value (comparison of groups) | 0.9728 | 0.9997 | x | 0.9997 | 0.9342 | x | |||
Table 6.
Quality of life assessment according to the DCFC scale before and after therapy in the compared groups.
Table 6.
Quality of life assessment according to the DCFC scale before and after therapy in the compared groups.
| Group | Measures | DCFC | p-Value | Cohen’s d | |
|---|---|---|---|---|---|
| Before Therapy | After Therapy | (Before vs. After) | |||
| Study group | Mean ± SD | 24.91 ± 5.12 | 14.71 ± 4.16 | <0.0001 | 3.5926 |
| Me [Q25; Q75] | 24.5 [22; 27.75] | 14 [11.25; 17] | |||
| Min; Max | 16; 36 | 9; 23 | |||
| Control group | Mean ± SD | 27.81 ± 6.68 | 23.81 ± 5.62 | 0.0001 | 1.9516 |
| Me [Q25; Q75] | 27.5 [22; 32.25] | 23.5 [20; 27.25] | |||
| Min; Max | 16; 44 | 15; 38 | |||
| Level p (comparison of groups) | 0.3559 | <0.0001 | x | ||
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Milewska, A.; Przedborska, A.; Irzmański, R. Assessment of the Impact of Training Using the Luna-EMG Rehabilitation Robot on the Functional Status of Patients After Total Hip Replacement: A Randomized Trial. Appl. Sci. 2025, 15, 11065. https://doi.org/10.3390/app152011065
AMA Style
Milewska A, Przedborska A, Irzmański R. Assessment of the Impact of Training Using the Luna-EMG Rehabilitation Robot on the Functional Status of Patients After Total Hip Replacement: A Randomized Trial. Applied Sciences. 2025; 15(20):11065. https://doi.org/10.3390/app152011065
Chicago/Turabian StyleMilewska, Aleksandra, Agnieszka Przedborska, and Robert Irzmański. 2025. "Assessment of the Impact of Training Using the Luna-EMG Rehabilitation Robot on the Functional Status of Patients After Total Hip Replacement: A Randomized Trial" Applied Sciences 15, no. 20: 11065. https://doi.org/10.3390/app152011065
APA StyleMilewska, A., Przedborska, A., & Irzmański, R. (2025). Assessment of the Impact of Training Using the Luna-EMG Rehabilitation Robot on the Functional Status of Patients After Total Hip Replacement: A Randomized Trial. Applied Sciences, 15(20), 11065. https://doi.org/10.3390/app152011065
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
