DOI: 10.31038/IMROJ.2021634

Abstract

We have visually described and analyzed by means of quantifed EEG (qEEG) a highly unusual EEG pattern, not associated with cognitive or any other symptomatology. This pattern consists in an asymmetric highly stationary and highly synchronized trace through all the scalp, mainly composed by alpha-band rhythms. This anomalous pattern appears during quiet-basal and active wakefulness and alternates with more physiological patterns.

We demonstrate that there are not features of epileptic or irritative and show that alpha rhythms are the main component of this pattern. Conclusion: it is essential to be familiarized with objective and numerical measures in EEG clinical practice to sustain results that can be related with basic neurophysiological research. Just approaches like this, we will increase the theoretical foundations of EEG, improving its utility and increasing its accuracy.

Keywords

Alpha rhythm, Quantified EEG, Scalp EEG, Synchronization

Introduction

The electroencephalogram (EEG) during relaxing wakefulness is dominated by alpha rhythm, maximum at occipital lobes when eyes are closed [1]. There is an increasing evidence that it is linked to important aspects of perception, as maximal interstimulus interval for perceived simultaneity or reaction time [2,3]. Alpha activity is also present at central regions, where is known as mu-rhythm. However, other cerebral rhythms are present to at different scalp regions [4,5]. Several kinds of EEG patterns have been described, both in physiological and pathological conditions by means of de visu description and by means of quantitative EEG (qEEG). This method allows an objective description of several features and can be extremely helpful, especially when patterns are highly complex [6-9].

EEG is especially adequate to study epileptic condition, both during interictal as during ictal states. Irritative activity is a synonymous of epileptiform activity and its morphology denotes cortical hyperexcitability. Generally, it is spike-like shaped, with a faster ascend than descend phase, associated with some background slowness and monopolar or dipolar field configuration, at least when activity is focal [10]. Among irritative patterns is the fixation-off sensitivity (FOS), characterized by: i) occipital or generalized epileptic discharges, ii) that constantly occur after closing the eyes and last as long as the eyes are closed and iii) they are induced by the elimination of central vision and disappear with fixation [11,12].

EEG is highly effective to discriminate between irritative and non-irritative activities, although sometimes this is difficult, especially when pattern is not common or well described. In this case, qEEG can be extremely useful [7]. In this work, we describe and quantify an EEG pattern highly unusual during wakefulness and misdiagnosed as FOS and epileptic, probably by the unusual of presentation. We demonstrate that there are not features of epileptic or irritative and show that alpha rhythms are the main component of this pattern.

Materials And Methods

Clinical Case

A 41-year-old female, right hand dominance with premorbid conditions of hypothyroidism, irritable bowel syndrome, chronic migraine, and epilepsy was admitted telemetry unit for presurgical evaluation. In a different center was diagnosed as generalized epilepsy with FOS. Te patient was being treated with 3 antiepileptic drugs.

Study was made with fully informed consent as specified by the Declaration of Helsinki and approved by local La Prinesa review board.

EEG Recording and Quantification

EEGs records were performed using a 32-channel digital system (EEG32U, NeuroWorks. XLTEK®, Oakville, Canada) with 19 electrodes placed according to 10-20 international system. In addition, the differential derivation I of Einthoven for ECG was placed. Recordings were performed at 512 Hz sampling rate, a filter bandwidth 0.5 to 70 Hz and notch filter at 50 Hz. Electrode impedances were usually below 15 kΩ.

Artifact-free periods (e.g. electro-oculogram -EOG- electromyography -EMG- or movement) were selected when possible and exported in ASCII file. Sometimes, analysis was done in the presence of some artifact (e.g. during non-basal awake state). The algorithm used has been previously published [7-9]. Briefly, areas under the power spectrum (PS), obtained by fast Fourier transform, were computed for classical EEG bands delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz) and beta (13-30 Hz). Stationary periods were mostly used to obtain average PS, although sometimes non-stationary periods were deliberately analyzed. Pearson’s correlation coefficient (r) was also calculated. One second Hanning windowing 10% superimposed were used to compute all of these measurements. Exported records were between 120 and 300 s, which allowed a minimum of 130 and a maximum of 330 windows to be computed. For every channel, the average and the standard error of mean (SEM) of whole the PS analyzed were computed. A group of 20 adults neither neurological pathology nor pharmacological treatment (43 ± 5 years-old) was used as control. Synchronization values form this group were probed to be gaussian by means of Kolmogorov-Smirnoff’s test. Comparison between patient’s PS and averaged from control group was assessed after normalization of all channels to the area of the occipito-parietal lobes (P3-O1/P4-O2). Numerical analysis of EEG recordings was performed with custom-made Matlab® R2019 software (MathWorks, Natic, MA, USA).

Statistical comparison with control group was performed using the Student’s t-test because normality was probed. However, when normality failed, the Mann-Whitney test was used. When possible, paired data were used. The significance level was set at p = 0.05.

Results

De visu Description of EEG

De visu basal eyes-closed EEG showed an apparently symmetric high-voltage pattern, highly homogeneous without antero-posterior gradient (Figure 1A). Periods of several minutes showed a high stationarity (Figure 1A). Eyes opening sometimes removed this pattern, returning after closing eyes back (Figure 1B), but not always. Neither real spikes nor sharp-waves were observed (Figure 1C). Hyperventilation o photic stimulation did not modify the pattern. We have named this state as shyncronized (EEGsyn). Neither signs nor symptoms were claimed during the long-lasting periods of EEGsyn recorded.

During active wakefulness, sometimes EEG showed a physiological desynchronized pattern (Figure 1D and 2C). However, this desynchronized pattern (EEGdesyn) usually alternated with EEGsyn even during periods of mental work (e.g. reading or watching screen, see below). Patient stayed more than 50% of wakefulness period in EEGsyn.

Figure 1: De visu description of wakeful trace. A) Medium-lasting trace during EEGsyn in basal state (eye closed) near 1 minute duration. A high amplitude, apparently symmetric and without antero-posterior gradient pattern is evident. B) Disappearing of EEGsyn pattern after eyes closure (EC) and re-appearing after eyes opening (EO). Only channels from right hemisphere are shown. C) Detail of the boxed-period form figure A. Neither spikes nor sharp-waves or any other epileptic elements are present. D) Physiological desynchronized pattern during active wakefulness. Short-lasting, small amplitude burst of alpha rhythm are present at occipital lobes.

Some anomalies in physiological responsiveness have been observed, as the blocking of mu rhythm with eyelid (Figure 2A), although a more frequent physiological vanish with movement of the contralateral upper limb has yet been observed (Figure 2B).

As previously stated, FOS appears always eyes are closed. However, this was not the case, because sometimes a truly physiological alpha rhythm vanished after eyes opening and appeared after eyes closing (Figure 2C). Moreover, EEGsyn pattern did not disappeared with gaze fixation, on the contrary, a highly stationary pattern remains during long-lasting periods of reading or gaze fixation onto screen.

Figure 2: De visu description of some properties during EEGdesyn. A) Anomalous blocking of right mu-rhythm with eyes closing, indicated by EOG potential. B) Physiological vanishing of mu-rhythm with movement of contralateral hand (arrow). C) Physiological EEGdesyn pattern with a suitable antero-posterior gradient and an alpha occipital rhythm during eyes closure (EC), adequately blocked by eyes opening (EO).

Numerical Characterization of EEG

Normalized PSs from basal resting state of EEGsyn was compared with the average from control-group. From Figure 3A we can observe a pattern completely different from control group (black lines), not only for the slower peak of posterior dominant rhythm, but for the great difference between anterior and posterior regions. In fact, in frontal and temporal lobes there is a significant reduction of delta activity. Although can be an effect of the channel used to normalization, what is clear is the great difference between physiological PS and those obtained from EEGsyn.

From Figure 3B we can observe the absence of physiological antero-posterior gradient. Through all the scalp there is three well-defined main components, one at 5.5 Hz in the theta band and two others in the alpha band at 9 and 11.5 Hz. The posterior dominant frequency (PDF) is 9 Hz. A faster component at 18 Hz (beta band) can be observed at occipito-temporal regions and can be a harmonic of PDF. Another relevant fact is that, although not observed from de visu description (Figure 1A), there is a great asymmetry between hemispheres, especially for parieto-occipital regions. Finally, it is remarkable the magnitude of PS, ranging even up to 400 µV²/Hz, at least one order of magnitude higher than usual PS.

Figure 3: Anomalous structure of EEGsyn. (A) Comparison between average normalized PS from control group (black lines) and normalized PS from patient; (B) Detailed comparison between PS from patient. Dotted lines mean SEM. Red lines = right hemisphere; Blue lines = left hemisphere. Vertical lines mark frequencies of the most relevant components at 5.5, 9 and 11.5 Hz. Y-axis units in µV2/Hz.

We have coined the term synchronized for this pattern because r values for whole hemispheres were higher than for control group. However, not all the regions were hypersynchronized than control group. In fact, left frontal and parieto-occipital lobes were relatively desynchronized, as can be observed from Figure 4. It’s also notably the significant asymmetry in synchronization between hemispheres for frontal and parieto-occipital lobes at all the three states (p < 0.001 for paired Student-t test).

Figure 4: Average synchronization at several states for different regions for (A) left and (B) right hemisphere. Black = control group; red = EEGsyn in basal state; green = EEGsyn during active awake; yellow = EEGdesyn. *** p < 0.001 for Student-t test between control group and EEGsyn.

Hypersynchronized state not only appeared during closed eye periods, but also during cognitive task-performance (e.g. reading, writing, or watching t.v.). During these periods, de visu appearance of trace and PS was similar to that of basal state (Figure 5), as was also the mean PSs for channels. The main difference is the disappearence of the higher alpha components at fronto-polar regions (11 Hz) and the slight increase of the mean generalized alpha component to 10 Hz. The theta 5 Hz component is also present at both states. However, as can be observed from Figure 4, r average was higher (p < 0.001, Mann-Whitney test) for both hemispheres with similar values for frontal lobes, but desynchronization in left parieto-occipital (p < 0.001 Mann-Whitney test) and temporal lobes (p < 0.05 Mann-Whitney test) and hypersynchronization for right parieto-occipital (p < 0.01 Mann-Whitney test) and temporal lobe (p < 0.001 Mann-Whitney test).

Figure 5: Similar pattern during EEGsyn states. (A) Raw traces from quiet wakeful basal eye-closed state and (B) from active wakeful eye-open state. (C) Superposition of average PS for both states at every channel from left (D) and right hemisphere. Thick lines from quiet and thin line from active states respectively. Vertical lines are the same that in Figure 3B. Delta component during active EEGsyn at anterior regions reflects artifact from EOG.

Alpha Dependence of EEGsyn

We have addressed how EEGsyn appeared from EEGdesyn state. As can be observed for every state, alpha activity is remarkably similar for occipital and central regions (mu-rhythm). This late component spreads over neighbor regions, mixing with occipital dominant rhythm until affect whole scalp (Figure 6A). The generalized alpha component of PS but mainly located at frontal lobes (mu-alpha rhythm) increased clearly for all channels around the 10 Hz dominant frequency. The only component of new apparition during EEGsyn was the 5 Hz theta component asymmetrically distributed (Figure 6B and 6C). This last component, as stated above was always present during EEGsyn states, quiet and active.

Figure 6: Evolution from mu-alpha rhythm during EEGdesyn. (A) Raw traces during wakeful active eye-open state (EEGdesyn) showing mu-alpha and alpha occipital rhythms (left column at t = 0 s), 30 s later (middle column) and at 120 s (right column), when EEGsyn pattern is present. (B) Superposition of average PSs at different times for channels from left and (D) right hemisphere. Thick lines = 0 s; sliced line = 30 s; dotted-sliced = 70 s and dotted line = 120 s. Vertical lines are the same that in Figure 3B. Delta component during active EEGsyn at anterior regions reflects artifact from EOG.

During active wakefulness with mental activity sudden transitions between EEGsyn and EEGdesyn were observed (Appendix, Figure 1). The most dramatic change observed during these transitions was a decrease in alpha and in a lesser degree, beta bands (see Appendix, Figure 1C and 1D).

Discussion

We have described and analyzed a highly unusual EEG pattern, not associated with cognitive or any other symptomatology. This pattern consists in an asymmetric highly stationary and highly synchronized trace through all the scalp, mainly composed by alpha-band rhythms. This anomalous pattern appears during quiet-basal and active wakefulness and alternates with more physiological patterns.

The regulation of the EEG bands is carried out by different brain structures [13,14]. This complex neuroanatomic homeostatic system is probably genetically determined and regulates baseline levels of local synchronization, global interactions between different regions and spectral composition of the signal [15-18]. It is commonly believed that beta activity is originated from cortico-cortical interactions, meanwhile alpha implies thalamo-cortical activity. According to the International League against Epilepsy, an epileptic seizure is a transient occurrence of signs and/or symptoms due to abnormal excessive or synchronous neuronal activity in the cortex of the brain [19]. Therefore, we must expect that ictal activity would be associated with increase in the frequency of scalp activity, by increasing the beta activity [7]. We have showed that the EEGsyn pattern is composed by an asymmetric mixture of theta to beta components not changing during long period of time. In fact, there is a pattern highly stationary, not changing its PSs practically nothing during periods as long as tens of minutes. Synchronization, although higher than control, neither changes along the time. Therefore, once the pattern is stablished from EEGdesyn, neither evolution of frequency nor synchronization change is observed. This highly stationary pattern is not compatible with epileptic seizure dynamics [20,21]. Taking into account that EEGsyn was present during more than 50% of wakefulness and neither cognitive nor behavioral symptoms/signs were observed, no epileptic features can be associated with this state. Therefore, we can rule out that this would be a kind of ictal pattern.

In the same way, we must discard EEGsyn as FOS, and therefore as irritative. We have shown that waveforms have not irritative morphology, pattern does not constantly occur after closing eyes, in fact frequently appears during eyes opening and does not disappear with gaze fixation, and on the contrary, it’s commonly present during reading or watching screens. Therefore, none of the features defining FOS are present at EEGsyn pattern [11,12].

There is increasingly evidence showing that alpha rhythms are generated at thalamus [22-24] although the participation of occipital cortex is debated [25]. In fact, alpha, theta and also delta frequencies are elicited by acetylcholine and glutamate at thalamic lateral geniculate talamo-cortical (TC) neurons [22]. In mammal models, a convincing model of interplay between TC rely cells and interneurons, coupled by gap junctions and chemical synapses has been described [24]. It can be speculated that an abnormal network of TC neurons/interneurons (not necessary viewed as a morphological alteration) can be responsible of the EEGsyn pattern in this patient. This could explain why despite the anomalous structure of the EEG, neither cognitive complaint nor behavioral changes are observed during the pattern. Obviously, more studies would be needed to try this hypothesis (e.g. functional connectivity by MR, detailed cognitive evaluation or evoked potentials at different states).

To the best knowledge of authors, this pattern has not been previously described and we have not found beforehand in our experience (more than 25000 EEG along the last 25 years). Then, we do not expect that publish of this kind of pattern would be of great interest to neurophysiologists to keep in mind as a possible differential diagnosis. However, what is important in practical terms is to use objective concepts in EEG practice, allowing a differentiation between epileptic and non-epileptic patterns, because misdiagnosis can lead to an iatrogenic climbing with disastrous results for the patient. EEG is considered highly subjective (discussed at. [9]) and therefore, a basic theory of EEG is poorly developed. Therefore, it is essential to be familiarized with objective and numerical measures in EEG clinical practice to sustain results that can be related with basic neurophysiological research. Just approaches like this, we will increase the theoretical foundations of EEG, improving its utility and increasing its accuracy.

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Appendix

Figure 1: Fluctuation between EEGsyn and EEGdesyn during mental activity in awake state (A) Raw traces meanwhile the patient is reading at screen, change head to watch and hold the cellular phone (upper horizontal solid bar) and later return to reading onto screen; (B) Dynamical of EEG bands grouped by lobes during whole the period. Vertical lines denoted the change from screen to cellular phone. Red = right hemisphere; blue = left hemisphere; (C) Average PSs for all the tree periods from left and (D) right hemisphere. Thin lines = first EEGsyn period; thick lines = EEGdesyn (cellular phone) and dotted lines = second EEGsyn period. Observe that delta activity is due by EOG and is mainly located at fronto-temporal areas. Considering the active state of the patient, obviously there is no change in the eye movements during the three periods.

DOI: 10.31038/IMROJ.2021633

Abstract

Background: Stroke is an acute onset of neurological dysfunction due to abnormality in cerebral circulation with resultant signs and symptoms that correspond to the involvement of focal areas of the brain. Among all the neurological diseases of adult life, the cerebral vascular ones clearly rank first in frequency and importance.

Aim: To find out the effectiveness of over ground walking with treadmill gait training in right side subacute stroke subjects.

Settings and design: Physiotherapy Center, NIMHANS, Bangalore. Simple Random Sampling Technique used in this study.

Methods and material: 30 Subjects were selected on the basics of inclusion and exclusion criteria. All the subjects were divided equally into two groups; control Group and experimental Group. Before starting the training, pre-test scores are measured by using cadence and stride length. Control group received over ground walking and experimental group received over ground walking with treadmill gait training for 30 minutes, and both the groups received conventional therapy. At the end of five months, post-test scores of both groups were taken by used measure the cadence and stride length.

Results: Overground gait training with Treadmill gait training group post-test score (71.3, p<0.05) showed better improvements in mobility and gait speed, When compared to over ground gait training group (58.2.3, p<0.05).

Conclusion: The present study which proved that the use of body weight support treadmill training with partial body weight support combined with conventional physiotherapy to be more effective in improving gait ability in subacute subjects.

Keywords

Body weight support, Treadmill gait training, Gait speed, Mobility, Overground gait training

Introduction

Stroke refers to the sudden death of some brain cells due to a lack of oxygen when the blood flow to the brain is impaired by blockage or rupture of an artery to the brain [1].

Stroke may be manifested as Hemiplegia, which is the paralysis of muscles of one side of the body, contralateral to the side of the brain in which CVA occurred [2,3]. Clinically a variety of deficits are possible including the changes in the level of consciousness, impairments of sensory, motor, cognitive, perceptual and language functions. The locations of lesion, the extent of lesion, and the amount of collateral blood flow and early acute care management determine the severity of neurological deficits [4-6].

28% of stroke occurs in individuals under the age of 65 years. The incidence of Stroke is about 19% higher for males than females [7,8].

Stroke can be classified by etiological basis (Ischameic or Haemorrhagic), vascular basis (territory involvement), anatomical basis (cortical or brainstem or capsular or cerebellar or spinal), severity basis (minor or major) progression basis (completed or evolving) and onset basis (infantile or young or elderly stroke).

Stroke usually results in some degree of muscle weakness. It may lead to difficulty with producing force effectively within the context of a task and slowness to produce force is few of the commonest problems faced by the stroke subjects [9]. Moreover several studies have shown that muscle weakness is associated with reduced walking speed and endurance. And also muscle weakness has been suggested as a significant predictor of walking ability in stroke subjects [10].

Statement of Problem

Study on analyzing the effectiveness of Treadmill training with partial body weight support and physiotherapy in improving gait ability after stroke.

Need for the Study

Locomotion is one of the commonest problems after stroke in terms of asymmetry and reduction of speed etc. The most often stated goal for stroke subjects is to improve walking. For the improvement of walking, good strength of the lower extremity muscles is essential irrespective of the presence of spasticity because of growing evidence that muscle weakness rather abnormal reflex activity is a major limiting factor in physical function particularly for locomotor tasks following stroke. Through this study I would like to find out the effectiveness of body weight support treadmill training with partial body weight support and physiotherapy in improving gait ability of stroke subjects

Objectives

1. To determine the effect if body weight support treadmill training with partial body weight support and physiotherapy in improving gait ability of stroke subjects in group A subjects.
2. To determine the effect of body weight support treadmill training alone in improving gait ability of stroke subjects in group B.
3. To determine the difference between the effectiveness of body weight support treadmill training with partial body weight support and physiotherapy in improving gait ability of stroke subjects.

Materials Used in This Study

1. Treadmill
2. Supporting Harness
3. Set of pulleys
4. Couch
5. Pillows
6. Towels
7. Sand Bags
8. Swiss Ball
9. Parallel Bar

Methodology

Research Design

The design that is used for this study is experimental study design

Study Setting

Physiotherapy Center NIMHANS Bangalore

Study Sample

A total Number of 30 patient with stroke were selected by random sampling method with consideration of inclusion criteria and exclusion criteria and they were divided in to Group A and Group B.

Study Duration

All subjects participated in comprehensive 6 months Rehabilitation program.

A three week baseline study consisted of occupation therapy, and speech and neuro physiological therapy according to individual needs. During the subsequent 3 weeks of specific intervention gait training measured. Group A-Body weight support treadmill training with partial body weight support for 30 minutes 5 times a week. Group B – Body weight support treadmill training with partial body weight support for 30 minutes 5 times a week for 3 weeks.

Experimental Group (Group A): It consists of 15 subjects who underwent body weight support treadmill training and physiotherapy

Control Group (Group B): It consists of 15 subjects who underwent only partial body weight supported treadmill training.

Criteria for Selection

Inclusion Criteria: Subjects with all types of stroke.

1. Age group between 29-40 years.
2. Subjects of willingness of participate in the study.
3. Subjects with both right and left hemiplegia
4. Both genders.
5. Able to understand at least simple instructions.
6. No other orthopedic or neurological diseases impairing mobility.

Exclusion Criteria

1. Subjects with other musculoskeletal disorder.
2. Medically unstable.
3. Non Co-operative subjects.

Parameter Used

Functional ambulation category (FAC).

Interventions

The purpose of the treatment and aim of the study were explained subjects who are selected for the treatment. All patients signed the consent form before undergoing treatment program. Subjects in group A was treated with body weight support treadmill training with partial body weight support and conventional physiotherapy. Subjects in group B was treated with exclusive body weight support treadmill training with partial body weight support. The treatment was given for both groups for periods of 6 months.

Procedure

Subjects were supported in a modified parachute harness suspended centrally by a set of pulleys connected to a flexible spring.

At the beginning of the therapy, two therapists provided manual help to correct gait deviations. One therapist sitting by the paretic side facilitated the swing of the paretic limb, determined that its initial ground contact was made with the heel, and prevented knee hyperextension during mid stance and encouraged symmetry of step length and stance symmetry.

The second therapist stood on the treadmill behind the patient and facilitated weight-shift onto the stance limb, hip extension and trunk erection. Mean treadmill speed was 0.21 (range 0.15-0.30 m/s was reached and kept constant until the end. The mean BWS was 27% (range 20-30) of body weight at the beginning. The support whilst 10 subjects needed a support of 5-15% BWS until the end. Net walking a support of treadmill was approximately 20 min per session with a brief rest in the middle.

Results

The pre and post-test values were assessed for gait ability in Group A. the standard deviation was 0.4. The ‘t’ values were calculated for gait ability by paired ‘t’ test was 28.5 and it was more than table value 2.15 for 5% level of significant at 14 degrees of freedom (Figures 1, 2, Tables 1 and 2).

Figure 1: Mean and mean difference value for group A and group B.

Figure 2: Standard Deviation value for Group A and Group B.

Table 1: Mean and mean difference value for group A and group B.

Table 2: Standard Deviation value for Group A and Group B.

The pre and post-test values were assessed for gait ability in Group B. the standard deviation was 0.85. The ‘t’ vales were calculated for gait ability by paired ‘t’ test was 4.5 and it was more than table value 2.15 for 5% level of significance at 14 degrees of freedom (Figure 3 and Table 3).

Figure 3: Paired ‘t’ test values for Group A and Group B.

Table 3: Paired ‘t’ test values for Group A and Group B.

The calculated ‘t’ values by unpaired ‘t’ test was 8.5. The calculated’ values were more than the table value 2.05 for 5% level of significance of 28 degrees of freedom (Figure 4 and Table 4).

Figure 4: Un paired ‘t’ test Values for walking ability in Group A and B.

Table 4: Un paired ‘t’ test Values for walking ability in Group A and Group B.

The paired ‘t’ values have shown that body weight support treadmill training with partial body weight support combined with physiotherapy are more effective for the improving gait ability of subjects after stroke. The unpaired ‘t’ test values have shown that there is significant difference in showing improvement in gait ability of stroke subjects.

This study has proved the 3 week combination of body weight support treadmill training with BWS and physiotherapy effected a large improvement of a gait ability of non-ambulatory hemi paretic subjects than an exclusive 3- week treadmill therapy with BWS.

Discussion

This study has proved that The 3 week combination of body weight support treadmill training with conventional physiotherapy effected a large improvement of a gait ability of non-ambulatory hemi paretic subjects than an exclusive 3- week treadmill therapy with BWS.

Recently, Kwakkel et al. reported that greater intensity of leg rehabilitation improved gait ability and activities of daily living in acute stroke victims [11]. The key elements of their lower limb rehabilitation program were comparable with the physiotherapy within the present study.

Richards et al had shown that an additionally applied, task-specific program including body weight support treadmill training without body weight support resulted In a larger gait velocity in acute stroke victims 6 weeks after study onset as compared with a conventionally treated group who received less therapy [12,13].

The potential for motor recovery after stroke therefore seems to be limited, and subjects of group A probably reached this presumed level faster, i.e. the combined treatment of physiotherapy and body weight support treadmill training accelerated motor recovery [14,15]. Richards et al. also reported in the above mentioned study that differences in gait ability between the high and low-intensity group had waned at follow-up 6 months later, also because of a further improvement of a large extent in the low- intensity group.

Conclusion

From the results of this study 3 weeks of body weight support treadmill training with BWS pulls physiotherapy accelerated the restoration of gait ability in chronic hemi paretic subjects; correspondingly, a focused and intense treatment regime including locomotion training seems most promising in gait rehabilitation after stroke.

The result was analyzed using which proved that the use of body weight support treadmill training with partial body weight support combined with physiotherapy to be more effective in improving gait ability in hemi paretic subjects.

Limitation of the Study

1. This Study has been conducted on small size sample only.
2. The outcome of the study has been limited to improving gait ability only.

Recommendations

1. Further study may be extended with large sample.
2. Other aspect of motor impairment such as balance, strength may be considered.
3. The patient ability to either improve or retain the regained functional capacity may be assessed at regular intervals over a period of time.
4. The efficacy of this treatment may be found by altering the frequency and intensity.
5. The extended efficacy of these exercises may also be found out by increasing the total in duration of the treatment.
6. The body weight support treadmill training with partial body weight support may be applied to other neurological conditions such as Paraplegia.

References

1. Asanuma H, Keller A (1991) Neurobiological basis of motor learning and memory. Concepts Neuro Sci 2: 1-30.
2. Carr J, Shepherd R (1998) Neurological Rehabilitation. Butterworth & Heinemann, Oxford.
3. Collen FM, Wade DT, Bradshaw CM (1990) Mobility after stroke: reliability of measures of impairment and disability.
4. Dietz V, Colombo G Jensen L, Baumgartner L (1995) Locomotor capacity of spinal cord in paraplegic subjects. Ann Neurol 37: 574-582.
5. Grilner S (1985) Neurologic basis of rhythmic motor acts in vertebrates. Science 228: 143-149.
6. Hesse S, Berlet C, Schaffrin A, Malezic M, Mauritz KH (1994) Restoration of gait in non- ambulatory hemiparetic subjects by treadmill with partial body weight support. Arch Med Rehabil 75: 1087-1093.
7. Hesse S, Bertelt C, Jahnke MT, et al. (1995) Body weight support treadmill training with partial body weight support as compared to physiotherapy in non-ambulatory heparetic subjects. Stroke 26: 976-981.
8. Hesse S, Malezic M, Schaffrin A, Maurtiz KH (1995b) Restporation of gait by a combained body weight support treadmill training and multichannel electrical stimulation in non-ambulatory hemiparetic subjects. Scand J Rehabil Med 27: 199-205.
9. Holden MK, Gill KM, Magliozzi MR (1986) Gait assessment for neurologically impaired subjects.Standards for outcome assessment. Phys Ther 66: 1530-1539.
10. Jorgensen HS, Nakayama H, Raaschou HO, Olsen TS (1995) Recovery of walking function in stroke subjects:the Copenhagen stroke study. Arch Phys Med Rehabil 76: 27-32.
11. Kwakkel G, Wagenaar RC, Twisk JWR, Lankhorst GL, Koetsier JC (1999) Intensity of leg and arm training after middle cerebral artery stroke:a randomized trail. Lancent 354: 191-196.
12. Visintin M, Barbeau H, Korner-Bitensky N, Mayo NE (1998) Anew approach to retain gait in stroke subjects through body weight support and treadmill stimulation. Stroke 29: 1122-1128.
13. Werning A, Muller S (1992) Laufband locomotion with body weight support in persons with severe spinal cord injuries. Paraplegia 30: 229-238.
14. Lovely RG, Gregor RJ, Roy RR, Edgerton VR (1986) Effects of training on the recovery of full weight bearing stepping in the adult spainal cat. Exp Neurol 92: 421-435.
15. Visintin M, Barbeau H (1989) The effects of body weight support on the locomotor pattern of spastic paretic subjects. Can J Neurol Sci 16: 315-325.

DOI: 10.31038/IMROJ.2021631

As in many countries COVID-19 infection levels are high, consecutivly many patients develop the severe form of the disease whilst the capacity of clinics is limited. SARS-CoV-2 is acting unfortunately on different levels, once infected there is no single drug able to prevent the ongoing disease. I would like to share my personal experience because it might help to prevent lung damage with simple and available remedies.

March 2020, aged 52 years, I got infected two times, the 11th and the 17th, by a double exposition to SARS-CoV-2 during several hours. The onset of a severe clinical form of the disease followed. No PCR-test was possible at that time.

The 19th of March the symptoms started. They disappeared at about the 29th, but the 30th March retrosternal pain began associated to a beginning pulmonary dysfunction, accompagnied by serious neurologic troubles. I suffocated while breathing normally and therefore a hypoxemia was more than possible. Hypoxia means reactive oxygen (ROS) and reactive oxygen nitrogen species (RNOS) occur. In the meantime their interference in COVID-19 has been proven.

In the Center of Oxygen, Research and Development, where I worked during my PhD studies on hypoxia, ROS and RNOS, my fellow researchers and colleagues examined the antioxidant properties of vitamin C, E, selenium, curcumin and resveratrol. Reseveratrol is found in highest levels in red wine like Pinot Noir. With the beginning of the pulmonary dysfunction I started the intake of several nutrients present at home as I was not sure medical doctors in a clinic would accept my hypothesis.

The pulmonary function decreased in a spectacular way during three days and stabilized then. A week later the improvement started.

The therapy was threefold: Increasing blood oxygen saturation, sustaining enzymes such as the glutathione peroxidase and intake of antioxidants.

In order to charge the blood physically with more oxygen the respiration pattern was voluntary increased several times a day. This means, first determination of the basal respiration frequency. Increasing this frequency with ten to fifteen more breath takes per minute during three minutes. Returning to the basal frequency.

Theophylline is known to improve the acute moutain sickness, another form of hypoxemia (known to lead to loss of smell and taste). Black tea was part of the diet.

On one hand the hypothesis worked out, on the other hand it did not.

It did not work out, because in the morning hours of the 25th April 2020 one of three heart beats missed and the blood pressure regulation got completely dysregulated.

The cardiac issues needed medical care.

It did work out, because the lungs did not develop the COVID-specific lesions as observable in the two joined images resulting from a contrasted thoracic CT scan the 29th May 2020.

The 25th of April the access for the cardiac problems to the emergency unit of a local hospital has been declined due to a blood oxygen level of 96%, and 5th of May the same at another local hospital (97% oxygen blood saturation). A supplementary blood analysis at the 5th of May did no show any particularities other than a slight lymphocytosis, slightly increased basophiles, a neutropenia and an insufficient vitamin D level. The level of SARS-CoV-2 antibodies was negative.

The remaining effects of the SARS-CoV-2 infection are the heart issues and a slight tinnitus of the left ear. SARS-CoV-2 specific T-cells are not yet examined. Another blood sample of the 10th December presents high levels of Gamma-globulins, indicating the presence of non-specific antibodies. EBV has been excluded.

Taken together, it could be interesting to add antioxidants to the therapy of COVID-19 in order to prevent lung damage, especially when no other medical care is possible.

Please find below a list of nutrients:

Supplementation of nutrients:

Vitamin B1:                          1,1 mg

Riboflavin:                            2,8 mg

Niacin:                                  16 mg

Pantothenic acid:                    6 mg

Vitamin B 6:                          1,4 mg

Biotin:                                  50 µg

Folic acid:                              200 µg

Vitamin B 12:                        12,5 µg

Vitamin C:                            1800 mg

Vitamin D:                            10 µg

Vitamin E:                             12 mg

Calcium:                                400 mg

Iron:                                     10 mg

Zinc:                                     5 mg

Selenium:                              55 µg

Iodine:                                 100 µg

Diet

Darjeeling/Earl Grey: 600 ml

Pinot Noir (Aigle Noir, Gérard Bertrand, Pays d‘Oc, 2019): 350 ml

Herbal infusion (1,75 g : 55% curcumin, 14% cinnamon, apple, 7% ginger, cardamom, 3% stevia leafs, fennel, nutmeg, cocoa shell 2%, black pepper, cloves)

Dark chocolate (85%): 25 to 50 g

In undetermined amounts: peanuts, olive oil, almonds, curcumin, fatty fish.

References

1. Pritom Chowdhury, Anoop Kumar Barooah (2020) Tea Bioactive Modulate Innate Immunity: In Perception to COVID-19 Pandemic. Review; Front Immunol 11: 590716. [crossref]
2. PT Goud, D Bai, HM Abu-Soud (2021) A Multiple-Hit Hypothesis Involving Reactive Oxygen Species and Myeloperoxidase Explains Clinical Deterioration and Fatality in COVID-19. Review. Int J Biol Sci 17: 62-72. [crossref]
3. M Iddir, A Brito, G Dingeo, SS Fernandez Del Campo, H Samouda , et al. (2020) Strengthening the Immune System and Reducing Inflammation and Oxidative Stress through Diet and Nutrition: Considerations during the COVID-19 Crisis. Review. Nutrients 12: 1562. [crossref]
4. L Loffredo, F Violi (2020) COVID-19 and cardiovascular injury: A role for oxidative stress and antioxidant treatment? Int J Cardiol 312: 136. [crossref]
5. Montserrat M, E de Gregorio, C de Dios, V Roca-Agujetas, B Cucarull, et al. (2020) Mitochondrial Glutathione: Recent Insights and Role in Disease. Review. Antioxidants 9: 909. [crossref]
6. M Mrityunjaya, V Pavithra, R Neelam, P Janhavi, PM Halami, et al. (2020) Immune-Boosting, Antioxidant and Anti-inflammatory Food Supplements Targeting Pathogenesis of COVID-19. Front Immunol 11: 570122. [crossref]
7. BB Muhoberac (2020) What Can Cellular Redox, Iron, and Reactive Oxygen Species Suggest About the Mechanisms and Potential Therapy of COVID-19? Front Cell Infect Microbiol 10: 569709. [crossref]
8. J Saleh, C Peyssonnaux, KK Singh, M Edeas (2020) Mitochondria and microbiota dysfunction in COVID-19 pathogenesis. Mitochondrion 54: 1-7. [crossref]
9. F Silvagno, A Vernone, GP Pescarmona (2020) The Role of Glutathione in Protecting against the Severe Inflammatory Response Triggered by COVID-19. Antioxidants (Basel) 9: 624. [crossref]
10. J Wu (2020) Tackle the free radicals damage in COVID-19. Nitric Oxide 102: 39-41. [crossref]