Potential Effects of Computer-Based Cognitive Training on Postural Stability and Locomotion in Parkinson’s Disease Patients: A Randomized Controlled Trial
1Department of Physical Therapy for Neurology and Neurosurgery, Faculty of Physical Therapy, Cairo University, Giza, Egypt
2Department of Neurology, Faculty of Medicine, Cairo University, Giza, Egypt
3Department of Basic Sciences, Faculty of Physical Therapy, Delta University for Science and Technology, Dakahlia, Egypt
4Department of Physical Therapy, College of Applied Sciences, Qassim University, Al Qassim, Saudi Arabia
5Department of physical Therapy for Pediatrics, Faculty of Physical Therapy, South Valley University, Qena, Egypt
6Department of Physical Therapy for Pediatrics, Faculty of Physical Therapy, Badr University in Assiut, Assiut, Egypt
7Department of Physical Therapy and Health Rehabilitation, College of Applied Medical Sciences, Jouf University, Al Qurayat, Saudi Arabia
Correspondence: Engy BadrEldin S. Moustafa Department of Physical Therapy for Neurology and Neurosurgery, Faculty of physical Therapy, Cairo University, 7 Ahmed ELzayat St. Bien Elsarayat, Dokki, Giza 11432, Egypt. Tel: +2 02 37617691 Fax: +2 02 37617692 E-mail: engybm.saleh@cu.edu.eg
• Received: April 27, 2025 • Revised: July 24, 2025 • Accepted: August 7, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
To examine the short-term and long-term effects of computer-based cognitive training on postural stability, locomotion, and cognitive performance in Parkinson’s disease (PD) patients.
Methods
Sixty-eight PD participated in this randomized-controlled trial, were randomly allocated into two groups; control group (GA) received a designed physiotherapy program for 60 minutes, and an experimental group (GB) got 30 minutes physiotherapy program as GA, along with 30 minutes of computerized cognitive training. Treatment sessions were three times/week for eight weeks. Primary outcomes were balance and spatiotemporal gait parameters; cognition was a secondary outcome. Primary and secondary measures were examined at baseline, immediately post-treatment, and three months post-treatment.
Results
From baseline to post-treatment, GB showed greater reductions in postural sway compared to GA. The mean differences in stability indices were 1.461±1.240, 0.982±1.185, and 1.006±0.982 in GB, vs. 0.581±1.503, 0.426±1.459, and 0.374±1.072 in GA. For gait parameters (gait velocity, stride length, and cadence), GB demonstrated larger improvements, with mean differences of -0.361±0.245, -0.242±0.158, and -11.606±12.628, compared to -0.155±0.254, -0.191±0.248, and -4.516±10.773 in GA. PD-Cognitive Rating Scale improved more substantially in GB (-16.091±6.978) than in GA (-1.129±4.552). These gains in postural stability, gait, and cognition were statistically significant (p<0.001) and sustained at the 3-month follow-up.
Conclusion
Computerized cognitive training as an add-on in the rehabilitation of PD is efficient in improving postural stability and locomotion, as well as the cognitive performance. The consistency of these findings for 3 months is an imperative point in the clinical course of PD patients.
Parkinson’s disease (PD) is a widespread progressively deteriorating neurodegenerative disorders worldwide. Dopamine insufficiency is the primary precursor that affects specific deep brain regions like the substantia nigra and basal ganglia [1]. The Middle East and North African regions had 309.9 thousand prevalent instances of PD in 2019, with a 15.4% rise since 1990 [2]. Resting tremor, bradykinesia, stiffness, and postural instability are the cardinal motor features of PD, along with a wide range of non-motor characteristics including psychological, sleep, vegetative, and cognitive disorders with a subsequent deterioration in the quality of life [3].
Postural stability and locomotion problems are the most irritating manifestations in PD patients, which typically get worse over time. Research suggests that postural instability is most closely accompanied with increased falls and elevation of mortality and morbidity in PD population [4]. Balance control depends on a complex network, which demands integrating information from different sensory systems for the motor adjustments [5]. In normal instances, balance is automatically controlled and mostly depends on sub-cortical systems such as the brainstem, basal ganglia, and cerebellum, however, excessive suppression of the motor and premotor areas as well as disruption of subcortical pathways cause PD [6]. Consequently individuals with PD usually depend on compensatory methods, such as elevating the sensory input, attention/concentration, and cognitive demands, for the successful accomplishment of a particular motor task [7].
One of PD major non-motor symptoms is cognitive impairment, which is an indicator of executive function inadequacy, where mild cognitive impairment representing up to 60% of the prevalence rate. Cognitive impairments in PD are usually accompanied with defective quality of life and elevated rates of disability and mortality, since they are among the most subsequent attributes of the disease [8]. PD patients with deficits in global cognitive function (particularly attention & concentration) showed severe gait impairments represented by postural instability and freezing of gait. On the other hand, visuospatial impairments were correlated with severe gait freezing, while higher postural instability was associated with poorer memory function [9]. In individuals with PD whose primary symptom is postural stability, impairment of the executive functions is a common sign; this relationship is significant since executive functions are correlated to other motor control activities as planning, motor coordination and anticipatory postural adjustments [10].
Computerized cognitive rehabilitation based on the execution of repeated computer-based tasks that involves specific skills [11]. It is considered a motivational stimulus likewise the majority of tools using audio-video feedback. Additionally, these tools permit adjustments in the duration, task category, and complexity of the assessments to align the intervention with the person’s skills. In order to prevent frustration caused by tasks that are either too simple or too complicated, the exercises are assigned based on the cognitive domain that is stimulated and difficulty level is tailored according to the patient’s level [12]. It has been shown that inventive interventions, such as computer-based therapies, could be used to restore cognitive function by simulating diverse cognitive domains, which would increase the patient’s motivation, also when compared to traditional cognitive training (using paper and pencil), computerized cognitive training demonstrated beneficial for PD individuals with minor cognitive impairments [13]. Despite the various privileges of computerized cognitive approaches, there are diverse limitations accompanying the use of these devices such as the need for computer skills; photosensitive issues; acceptability and availability of the devices. However, there are neither explicit recommendations nor cautions regarding the use of this approach [14].
The current study is an attempt to provide alternative therapies for people with PD, it is crucial to look into approaches that allow intermingling between motor and cognitive tasks particularly since a correlation between impairments of balance and cognitive dysfunctions has been proven [9,10]. Early diagnosis is mandatory for proper management of these abnormalities and rehabilitative outcomes. Therefore, the optimum standard in managing PD includes a mix of cognitive, motor, and dopaminergic therapy as well as occupational therapy [15,16]. As far as we know, no previous researches in the literature are comparable to the one proposed in this clinical trial, that labels and verifies the efficacy of adding computerized cognitive training to a designed rehabilitation program on postural stability, spatiotemporal gait parameters and motor symptoms in patients with PD; adding to this investigating the long-term proficiency of both interventions after 3-month follow-up.
METHODS
Design of the study
A randomized, follow-up, controlled study. Participants were randomized into 2 parallel groups with allocation ratio 1:1; where a real computerized cognitive training compared to a conventional physical rehabilitation program. The assessor and the patients were blinded to the groups’ allocation. Participants were recruited from Department of Neurology, Faculty of Medicine, Cairo University and the study was handled in the cognition training lab at Faculty of Physical Therapy, Cairo University, between May 2024 and February 2025. This study was approved by the Ethics Committee of Faculty of Physical Therapy, Cairo University (P.T.REC/012/004746) and carried out in compliance with the Declaration of Helsinki's ethical guidelines. The ethics committee waived the need to obtain specific patient consent due to the nature of the study, in accordance with applicable institutional rules and ethical requirements. The study was prospectively registered with ClinicalTrials.gov (NCT06104072).
Randomization and masking
Randomization was conducted via sealed envelopes by an external assessor. To avoid bias, treatment was executed by one therapist while assessment was applied by another therapist who was oblivious to the patients’ group allocation.
Participants and selection criteria
Participants’ selection were according to the following criteria; age, 55 to 70 years; a verified clinical diagnosis by a neurologist and computed tomography, attained the UK criteria for diagnosis of idiopathic PD [17], duration since onset of PD is from two to five years [18]. Patients with mild to moderate PD manifestations in accordance with Unified Parkinson’s Disease Rating Scale (UPDRS) part III motor subscale (scoring between 20–35) [19] and stages (2.5&3) in modified Hoehn and Yahr (H&Y) scale were included [20]. Patients with mild cognitive impairment were included according to Parkinson’s Disease-Cognitive Rating Scale (PD-CRS); scores (65–81) [21]. Exclusion criteria were other neurological conditions that may affect gait, balance, and cognition, secondary parkinsonism (medications or illness that cause manifestations similar to PD), aphasic patients, severe physical, visual, or auditory impairment affecting the test completion, severe musculoskeletal disorders such as lower limb fractures, fixed deformities, total replacements of lower limb joints, severe arthritis, knee surgeries, use of any drugs that could influence cognition (e.g., donepezil, rivastigmine, and galantamine, etc.), current use of medications that affect alertness as sedative, neuroleptic or anxiolytic medications or sleeping aids, intractable or illiterate patients.
Treatment interventions
The intervention program consisted of 24 sessions for both groups applied as follows; 3 times per week, 60 minutes per session, for eight consecutive weeks, and to compensate any absence or skip in the sessions it was extended to 10 weeks. A designed physical therapy program was delivered to all patients in both groups, which included balance training on different surfaces with graduated stability, stretching for upper and lower limb as well as back flexors, postural correction, motor coordination, agility, anticipatory and reactive postural corrections, in addition to multi-directional gait training [22].
A designed physical therapy program was given to the control group (GA) for a whole 60 minutes, while for the experimental group (GB), Rehacom computerized cognitive training was conducted for 30 minutes as well the same physical therapy program as GA for 30 minutes. RehaCom cognitive rehabilitation software (HASOMED GmbH) is an extensive program relying on the use of computer systems for cognitive rehabilitation (https://hasomed.de/en/products/rehacom/). This software consists of therapeutic modules categorized into eight main groups, each with multiple subgroups [23]. Each Patient was asked to use the Rehacom custom panel, which is a particular type of keyboard with big, unsophisticated, and obvious keys. This personalized panel features six huge keys: two large green keys to confirm selection and four large white keys to go up, down, right, and left among the options displayed; two other keys (red one for urgent test termination and yellow one for inquiries about the procedure) and one joystick (Fig. 1) [24]. Four main cognitive domains were targeted in this study; figural memory, attention/concentration, visual response control, and auditory response control. Each cognitive domain includes hundred levels of difficulty for each test, with an average of 22 subtests. Tasks are auto-adjustable; therefore based on the way the patient answers questions, the degree of task difficulty is either automatically increased or decreased (Fig. 2) [25].
Outcome measures
All evaluations took place during the “on” period of the medicine (one hour after the treatment was administered). One external evaluator was responsible for the assessment for all the included patients. Primary outcomes were overall stability, medio-lateral stability, anteroposterior stability as well as spatiotemporal gait parameters including cadence, velocity, and stride length, while cognitive performance was the only secondary outcome. All assessments were administered to both groups at baseline, just after the intervention, and three months later.
Primary outcomes
(1) Multidirectional postural stability
A computerized balance platform, the Biodex Balance System (BSS) (Model 945-302, 3.12 software versuion; Biodex Medical Systems, Inc.) was used to assess; the anterior-posterior stability index (APSI) which indicates the patient’s capacity to regulate balance both forward and backward, the medio-lateral stability index (MLSI) that represents the patient’s ability to maintain balance sideways, as well as the overall stability index (OSI) indicates the patient’s capacity to regulate postural stability in many directions. Higher values indicate more balance disturbance. The system comprises a movable circular platform that tilts the surface in numerous directions from the horizontal plane by up to 20 degrees. The degree of the surface instability can be adjusted from minimum instability (level eight) to maximum instability (level one). The protocol, stability level, and test duration are chosen by the clinician. Individuals were instructed to keep the center of mass in the middle of a centered circle that is displayed on a screen in front of the patient [23,26].
(2) Spatiotemporal gait parameters (velocity, cadence and stride length)
A digital 2D video camera (Sony Cyber-Shot 14.1 Megapixels, Model No. DSC-W530, including a 2.7-inch LCD and a Carl Zeiss Vario-Tessar 4x Wide-Angle Optical Zoom Lens) was used to capture the patient’s gait in the sagittal plane [27]. The captured film was then analyzed using special motion analysis software (Kinovea); it is a computer-based program used for analysis, measurement, and comparison of motion videos. Each patient was asked to walk along the 10-meter walkway with the regular walking pattern and speed and do not stop walking except at the end of the walkway. The measured parameters were;
Velocity: the actual distance that the patient walked/time in seconds.
Cadence: the number of steps/minute, which was estimated by dividing the number of steps that the patient walked over the actual duration of walking.
Stride length: the distance from the first foot contact in the first frame to the ipsilateral foot’s subsequent first touch in the second frame.
Secondary outcomes
(1) Overall cognitive performance
PD-CRS, a specific neuropsychological scale was used for evaluating cognitive deterioration in patients with PD. It is a valid and reliable screening tool to measure PD-related cognitive decline [28]. There are nine tests or assignments total, with a maximum score of 134, as shown in (PD-CRS English & Arabic versions) (Supplementary Table S1).
Data analysis
Sample size determination
The sample size was determined using the following criteria: a two-tailed significance level (α) of 0.05 and an effect size of 0.5 indicate a moderate effect size according to Cohen’s criterion; an effect size f2 (V)=0.1363 with 2 independent groups using a power (1-β) of 0.80 to compare seven primary variable outcomes in order to lower the possibility of type II errors. The sample size was determined using G*Power 3.1 software, taking into account these characteristics and a previous study that received comparable treatments [12]. According to the computations, 29 persons each group (GA and GB) were advised in order to examine a notable difference with 80% power and a 5% level of significance; nevertheless, the number was raised to 34 participants per group, for a total of 68 participants in the study to consider the drop out from the time of patients’ group allocation to the end of the treatment protocol.
Statistical analysis
SPSS package version 25 for Windows was used to do statistical analysis (IBM Corp.). Shapiro–Wilk and Levene’s tests were used to evaluate the data’s normality and homogeneity. Since the data were homogenously distributed, parametric analysis was performed; data was expressed using the mean and standard deviation (SD). Numbers and percentages were used to express categorical data. The two groups’ baseline demographic and clinical characteristics were compared using Student t-tests for continuous data and χ2 testing for categorical data. Comparing the multiple dependent variables at the baseline, post-intervention and follow-up between both groups were applied using MANOVA. To compare each set of the measuring periods (baseline to post intervention, post intervention to follow-up, and baseline to follow-up), post-hock multiple pairwise comparisons were performed. Spearman’s rho correlation (r) was used to assess the correlation between postural and gait functions in relation to the enhancements in cognitive performance following the intervention. All statistical tests have a significance level of p<0.05.
RESULTS
Flow of participants and adherence to the study protocol
During eligibility screening a total of 100 participants underwent screening, 32 participants were eliminated; 15 patients rejected to join the study, 11 patients did not adhere to the inclusion criteria, and 6 patients weren’t able to withstand the cognitive training session. Sixty-eight levodopa-dependent PD from both sexes agreed to participate and met the inclusion criteria. Participants’ progress through the trial is shown in CONSORT flow diagram (Fig. 3). There was no drop-out to follow-up during the study.
Characteristics of the participants
Patients’ characteristics and demographics were assessed as part of the baseline examination and were presented descriptively in Table 1. Regarding age (years), weight (kg), height (cm), body mass index (kg/m2), disease duration (years), and UPDRS-motor score, both groups were homogeneous in the initial assessment. For H&Y scale staging and the sex distribution, both groups were homogenous in the percentage of patients’ distribution (Table 1).
For all of the evaluated primary and secondary outcomes, between-groups analysis showed no discernible differences between groups at the baseline assessment. See Table 2, the baseline mean values and SDs of the participants for stability indices, spatiotemporal gait parameters, overall cognitive performance, and UPDRS for Parkinson’s motor symptoms, where p˃0.05.
Effects of the intervention
In this study, for the tested groups effect, Wilks’ Lambda (Ʌ=0.216) which is quite low, indicating a large difference between the groups across the dependent variables. Partial eta² (ƞ2=0.784) indicating a very large effect size. This means 78.4% of the variance in the dependent variables is explained by group differences. For the group effect (F=29.004, p<0.001) which is statistically significant. The measuring period effect showed that (Ʌ=0.063) indicating very strong time-based differences (pre vs. post-intervention), partial eta² (ƞ2=0.937) reflecting an extremely large effect size, where 93.7% of variance is explained by the measuring period with F=51.782, p<0.001 reflecting a high significance. The Interaction Effect (group×time), Wilks’ Lambda was very low (Ʌ=0.139) proving that the groups behaved differently over time through the study, with very strong interaction effect (partial eta²=0.861), where 86.1% of variance explained the interaction effect between groups and time (F=21.639, p<0.001) reflecting a statistically significant interaction (Table 3).
Primary outcomes
There was reduction in the amount of postural sway represented by a marked decrease in all the Biodex stability indices in GB compared to GA (p<0.05), see post intervention mean values and SDs (Table 2). There was significant reduction in overall stability by 1.461 points compared to 0.581 points for the GA, for antero-posterior stability by 0.982 points compared to 0.426 points for the GA, and for medio-lateral stability by 1.006 points compared to 0.374 points for the GA, see the mean differences of the pairwise comparison (baseline to post-treatment) for both groups (Table 4).
There was improvement in the spatiotemporal parameters represented by an elevation in all the spatiotemporal parameters in GB compared to GA (p<0.05). See post intervention mean values and SDs (Table 2). Velocity increased by -0.361 points post intervention for the GB compared to -0.155 points for the GA, stride length increased by -0.242 points post intervention for the GB compared to -0.191 points for the GA, and cadence increased by -11.606 points for the GB compared to -4.516 points for the GA, see Table 4, the mean differences of the pairwise comparison (baseline to post-treatment) for both groups.
The follow-up measures revealed that the improvement gained post intervention in the stability indices and spatiotemporal parameters were maintained in favor to the GB (p<0.05), see follow-up mean values, SDs, and the base to follow (Table 4). However there was no further improvement in the follow-up findings in most of the primary outcomes for both groups compared to the post intervention findings, where p˃0.001, see post to follow (Table 4).
Secondary outcomes
The experimental intervention significantly improved overall cognitive performance represented by an elevation in PD-CRS scores only in GB (p<0.05), see post intervention mean values and SDs (Table 2). Post intervention PD-CRS scores increased by -16.091 points for the GB compared to -1.129 points for the GA See Table 4, the mean differences of the pairwise comparison (baseline to post-treatment) for both groups.
The follow-up measures revealed that the improvement gained post intervention in PD-CRS scores were maintained only in the GB (p<0.05), see follow-up mean values, SDs and the base to follow (Table 4). However there was no further improvement in the follow-up findings in the secondary outcomes for both groups compared to the post intervention findings, where p˃0.001, see post to follow (Table 4).
Interpretation of the outcomes in terms of minimal clinically important differences
Primary outcomes
For the postural stability, based on a previous study, a change of 0.22°, 0.26°, and 0.41° for OSI, APSI, and MLSI respectively was considered as the minimal detectable change when assessing balance using the BSS in PD patients and often interpreted as clinically meaningful [29]. Our findings revealed that, Baseline to post intervention mean differences for OSI, MLSI and APSI were 1.46°, 1.01°, and 0.98°, respectively. On the other hand, the baseline to follow-up mean differences for the same variables were 1.28°, 0.97°, and 0.9°, respectively. Accordingly, such post intervention and follow-up improvements suggest that the intervention produced not only statistically significant but also clinically relevant benefits in postural control for individuals with Parkinson’s disease.
Regarding the spatiotemporal parameters, the minimal clinically important differences (MCIDs) when assessing spatiotemporal gait parameters in patients with PD, for gait velocity ranged from 0.05 to 0.22 m/s while for stride length, it has been determined to be 3.6 cm (0.036 m) [30]. Our findings revealed that, baseline to post intervention mean differences for gait velocity and stride length were 0.357 m/s and 0.25 m respectively. On the other hand, the baselines to follow-up mean differences for the same variables were 0.31 m/s and 0.22 m respectively. Thus, the post intervention and the follow-up findings for the spatiotemporal parameters in PD patients had exceeded the MCID thresholds, which imply that the improvements were both statistically significant and clinically important.
Secondary outcomes
In PD-CRS, A 4.5-point change in total score has been proposed as the MCID in early to mid-stage PD patients [31]. The study findings showed that baseline to post intervention mean difference for PD-CRS was 16.1 points, while for the baseline to follow-up mean difference, it was 14.7 points. Therefore, the post-intervention and follow-up results for cognitive performance in PD patients had beyond the MCID criteria, suggesting that the changes were both clinically relevant and statistically significant.
Correlations between postural stability and gait vs. cognitive performance post-intervention
Spearman’s rho correlation (r) was used to assess the correlation between postural stability represented by (OSI, MDSI, APSI) scores and cognition represented by PD-CRS following the intervention in PD patients. Correlation coefficient between OSI scores and PD-CRS was r=-0.829, for APSI vs. cognition was r=-0.664, and r=-0.688 for the correlation between MLSI vs. cognition. This suggests that as cognitive performance improves, postural stability tend to improve as well (i.e., lower index scores), particularly for overall stability (OSI).
For the post intervention correlation between cognition (PD-CRS) and spatiotemporal gait parameters (represented by velocity, cadence and stride length), Spearman’s rho correlation (r) was used. The correlation between gait velocity scores and PD-CRS was r=+0.798, for stride length vs. cognition was r=+0.652, and r=+0.647 for the correlation between cadence vs. cognition. This suggests that enhancements in cognitive performance were accompanied with improvements in gait velocity, stride length and cadence.
DISCUSSION
Findings of the study proved that adding Rehacom computerized cognitive training to conventional physiotherapy is prioritized for the outcomes of balance, gait, and cognitive function in PD patients. Considering the time effect, it also showed immediate post-treatment benefits on all the assessed outcomes in addition to the consistency of the gained results for 3 months. Adding computerized cognitive training to a designed physical therapy program relied on the idea that balance is multimodal and that it is strongly recommended to reconcile various frameworks [32]. However, the results available in the literature on the best treatment indication are still divergent.
Some prior studies tried to compare the effect of motor rehabilitation vs. cognitive rehabilitation, they established a correlation between cognitive and motor training, by comparing two interventions; balance training vs. cognitive-motor activities using Nintendo Wii Fit, the study findings revealed improvement in overall stability, medio-lateral stability, cadence, and cognition for both groups [33]. Similar effects were observed in our investigation, with more focus on spatiotemporal gait metrics, balance, and cognition in Parkinson’s population.
Our findings demonstrated that the improvements in the balance domains were associated with consolidation of the gained results at the follow-up, these results agreed with a study that assured that the increased physical activity in response to multi-domain cognitive training, possibly due to effects of intermingling the cognitive training with physical training on the executive functions, however the long term effect was not examined [34]. For the spatiotemporal gait parameters, our findings agreed with the results of another study which claimed that computerized cognitive training using a designated “brain training” programs such as Sudoku, which targeted working memory, processing speed, and visuospatial skills positively improved gait performance in PD patients particularly gait freezing [35].
Regarding the cognitive abilities and disease course in PD patients, our results were congruent to another study that suggested that remote cognitive rehabilitation for PD patients, twice per week, for one hour, over 8 weeks is practicable, entertaining, and may help decelerate the deterioration of cognitive decline [36]. This also agreed with a study which conducted a six-week cognitive training program for PD, results showed improvement in the patients’ cognitive functions which consequently improve the quality of life [37].
In this study, the correlation coefficient findings revealed that higher cognition scores were associated with lower postural sway; this agrees with Fernandes et al. [38] who proved that executive functions can act as predictors of balance deficit in individuals with Parkinson’s disease. This highlighted the importance of cognitive training as preliminary part in the motor rehabilitation for PD patients with balance and gait problems. Our study also revealed that higher cognition scores were associated with increase in gait velocity, stride length and cadence as well; this concur with Geritz et al. [39] who claimed that PD showed change in the walking performance relatable to deficits in visuospatial and divided attention, with slower speed and shorter stride lengths particularly in walking situations with additional cognitive demand.
The clinical relevance of our study was proved in relation to the MCID findings of previous studies, where the post intervention and follow-up findings of postural stability, gait and cognition in this study exceeded the established MCID range suggesting that the treatment effect is not only statistically significant but also clinically meaningful for individuals with PD [29,30,31]. These findings reinforce the clinical value of computerized cognitive training in PD, this aligning with earlier evidence supporting its use in comparable contexts such as; combined physical executive interventions, multi-domain cognitive training, remote cognitive remediation therapy, and cognitive-motor dual task training aiming to reduce risk of falling and improve balance as well as the gait kinematics [34,35]. However, the long term efficacy of such interventions has not been examined; also it is necessary not to generalize the results broadly since the MCID values were derived from slightly different demographics.
The study findings are not conjuring with Akin et al.’s [40] study who claimed that 8-weeks program of motor-cognitive dual task program and motor-motor dual task training showed no remarkable difference on postural stability, falling possibilities, walking practicality and muscle strength in older adults. Also, this study disagrees with Terra et al. [11] who claimed that in terms of enhancing balance in PD patients, cognitive-motor therapy was not better than motor therapy.
The points of strength in our study can be listed as following: (1) the novel therapy method that blends computer-based cognitive training and motor training; (2) the planned clinical study is exclusive to PD patients in the literature; (3) the duration of the intervention (24 sessions); (4) the program’s attributes are direct, supervised, inexpensive, accurate and widely applicable in clinical settings; and (5) a three-month follow-up of the outcomes to evaluate the consistency of the gained results.
It is also necessary, to point out some important limitations in this study. The study findings cannot be applied to all PD patients, especially those who are in more advanced stages, only patients with mild cognitive deficits were included; cognition was evaluated only by the PD-CRS, gait assessment focused only on the spatiotemporal gait parameters without considering PD characteristic patterns of walking, such as stiff gait and freezing of gait.
Conclusion
This work provides evidence regarding the potential benefits of adding computer-based cognitive training to a traditional physical treatment program; at improving cognitive performance, postural stability, spatiotemporal gait parameters in PD patients. An additional noteworthy impact of computerized cognitive training was the retention of the gained results for 3 months and the possible ability of this intervention to retard progression to PD-dementia. These findings have implications for exercise prescription and cognitive training in the rehabilitation program of patients with PD, in consideration with the clinical practicality, simplicity and inexpensive nature of the suggested treatment.
CONFLICTS OF INTEREST
No potential conflict of interest relevant to this article was reported.
FUNDING INFORMATION
None.
AUTHOR CONTRIBUTION
Conceptualization: Moustafa EBS, Darwish MH. Methodology: Moustafa EBS. Investigation: El-Tamawy MS. Formal analysis: Khalifa HA. Project administration: Moustafa EBS, Darwish MH. Visualization: El-Tamawy MS. Writing – original draft: Moustafa EBS. Writing – review and editing: Darwish MH, El-Tamawy MS, Mazen MM, Abo-Zaid NA, Khalifa HA. Approval of final manuscript: all authors.
ACKNOWLEDGMENTS
For hosting the interventions in our study, the authors would like to thank all the coordinators in Kasr Al Ainy hospital and in the cognition lab, faculty of Physical Therapy, Cairo University. The authors also express their gratitude to all of the patients who took part in this research.
Rehacom computerized cognitive training different tasks. (A) Example of the figural memory task. (B) Example of the attention/concentration task. (C) Example of the visual response control. (D) Example of the auditory response control.
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Potential Effects of Computer-Based Cognitive Training on Postural Stability and Locomotion in Parkinson’s Disease Patients: A Randomized Controlled Trial
Fig. 1. Rehacom computerized device in the cognition lab.
Fig. 2. Rehacom computerized cognitive training different tasks. (A) Example of the figural memory task. (B) Example of the attention/concentration task. (C) Example of the visual response control. (D) Example of the auditory response control.
Potential Effects of Computer-Based Cognitive Training on Postural Stability and Locomotion in Parkinson’s Disease Patients: A Randomized Controlled Trial
Characteristic
Control group (GA) (N=34)
Experimental group (GB) (N=34)
p-value
Age (yr)
60.97±2.58
62.03±2.68
0.10
Weight (kg)
72.97±3.36
75.03±5.49
0.07
Height (cm)
164.23±4.83
165.48±5.04
0.28
Body mass index (kg/m²)
27.14±1.41
27.39±1.31
0.40
Disease duration (yr)
4.265±1.136
4.735±1.02
0.08
UPDRS-motor score
33.47±3.77
35.09±4.76
0.13
H&Y staging
Stage 2.5
16 (47.1)
14 (41.2)
0.63
Stage 3
18 (52.9)
20 (58.8)
Sex distribution
Male
21 (61.76)
24 (70.59)
0.44
Female
13 (38.24)
10 (29.41)
Variables
Time
Control group (GA) (N=34)
Experimental group (GB) (N=34)
p-value
Stability indices
Overall stability index
Baseline
4.56±1.15
4.73±1.05
0.534
Post treatment
3.98±0.97
3.27±0.66
0.001*
Follow-up
4.07±0.93
3.45±0.67
0.003*
p-value
<0.001*
<0.001*
Anterior-posterior stability index
Baseline
3.86±1.06
3.76±1.06
0.724
Post treatment
3.43±1.00
2.78±0.53
0.002*
Follow-up
3.49±0.95
2.86±0.58
0.002*
p-value
0.0007*
0.0001*
Medio-lateral stability index
Baseline
3.25±0.92
3.25±0.61
0.987
Post treatment
2.87±0.55
2.24±0.77
<0.001*
Follow-up
2.91±0.53
2.28±0.77
<0.001*
p-value
0.0018*
<0.001*
Spatiotemporal gait parameters
Velocity (m/s)
Baseline
0.50±0.21
0.49±0.13
0.801
Post treatment
0.65±0.15
0.85±0.21
<0.001*
Follow-up
0.65±0.15
0.82±0.20
<0.001*
p-value
<0.001*
<0.001*
Stride length (m)
Baseline
0.71±0.23
0.73±0.15
0.516
Post treatment
0.90±0.15
0.98±0.06
0.006*
Follow-up
0.88±0.12
0.95±0.08
0.004*
p-value
<0.001*
<0.001*
Cadence
Baseline
72.03±6.64
74.33±10.42
0.293
Post treatment
76.47±8.48
85.94±7.18
<0.001*
Follow-up
76.42±8.37
85.64±7.33
<0.001*
p-value
<0.001*
<0.001*
Cognition
PD-CRS score
Baseline
67.53±3.27
69.18±3.74
0.068
Post treatment
68.68±3.16
85.27±5.92
<0.001*
Follow-up
68.48±3.04
83.88±7.03
<0.001*
p-value
0.93
<0.001*
Source of variation
Wilks’ Lambda value
Partial eta2 (η2)
F-value
p-value
Tested groups effect
0.216
0.784
29.004
<0.001*
Measuring period effect
0.063
0.937
51.782
<0.001*
Interaction effect
0.139
0.861
21.639
<0.001*
Variable
Pairwise comparison
Control group (GA) (N=34)
Experimental group (GB) (N=34)
Mean difference±SD
95% CI
p-value
Mean difference±SD
95% CI
p-value
Overall stability index
Baseline–Post treatment
0.581±1.503
0.053, 1.103
0.002
1.461±1.240
1.027, 1.893
<0.001*
Baseline–Follow-up
0.481±1.477
-0.026, 1.002
0.008
1.285±1.245
0.846, 1.714
<0.001*
Post treatment–Follow-up
-0.100±1.341
-0.557, 0.377
0.550
-0.176±0.941
-0.508, 0.148
0.053
Anterior-posterior stability index
Baseline–Post treatment
0.426±1.459
-0.079, 0.939
0.009
0.982±1.185
0.567, 1.393
<0.001*
Baseline–Follow-up
0.371±1.423
-0.126, 0.866
0.04
0.906±1.208
0.479, 1.321
<0.001*
Post treatment–Follow-up
-0.055±1.381
-0.422, 0.542
0.418
-0.076±0.785
-0.193, 0.353
0.3
Medio-lateral stability index
Baseline–Post treatment
0.374±1.072
0.005, 0.755
0.008
1.006±0.982
0.666, 1.354
<0.001*
Baseline–Follow-up
0.335±1.061
-0.029, 0.709
0.017
0.976±0.982
0.627, 1.313
<0.001*
Post treatment–Follow-up
-0.039±0.764
-0.305, 0.225
0.088
-0.033±1.089
-0.369, 0.389
0.233
Velocity (m/s)
Baseline–Post treatment
-0.155±0.254
0.064, 0.242
<0.001*
-0.361±0.245
0.272, 0.443
<0.001*
Baseline–Follow-up
-0.154±0.252
0.065, 0.241
<0.001*
-0.335±0.234
0.249, 0.411
<0.001*
Post treatment–Follow-up
-0.001±0.208
-0.072, 0.072
>0.999
0.026±0.288
-0.123, 0.066
0.215
Stride length (m)
Baseline–Post treatment
-0.191±0.248
0.105, 0.278
<0.001*
-0.242±0.158
0.195, 0.305
<0.001*
Baseline–Follow-up
-0.170±0.233
0.096, 0.242
<0.001*
-0.218±0.164
0.157, 0.271
<0.001*
Post treatment–Follow-up
0.022±0.192
-0.088, 0.046
0.326
0.024±0.097
-0.086, 0.030
0.213
Cadence (No. of steps/min)
Baseline–Post treatment
-4.516±10.773
0.752, 8.248
0.035
-11.606±12.628
7.208, 16.008
<0.001*
Baseline–Follow-up
-4.419±7.686
1.752, 7.113
0.041
-11.303±12.708
9.089, 13.511
<0.001*
Post treatment–Follow-up
0.097±6.708
-2.482, 2.201
>0.999
0.303±11.913
-2.184, 1.963
0.088
PD-CRS score
Baseline–Post treatment
-1.129±4.552
-0.413, 2.768
0.513
-16.091±6.978
13.662, 18.531
<0.001*
Baseline–Follow-up
-0.935±4.716
-0.312, 2.972
0.935
-14.697±6.117
-1.458, 1.762
<0.001*
Post treatment–Follow-up
0.194±4.643
0.412, 4.663
>0.999
1.394±5.349
-1.291, 2.429
0.083
Table 1. Patient’s demographics and general characteristics for both groups
Values are presented as mean±standard deviation or number (%).
, Moshera H. Darwish, PhD1
