Modern gait rehabilitation –
where are we and where are we going?
After a short critical examination of the traditional strictly formalised therapy concepts, this article illuminates the essential cornerstones of modern gait rehabilitation. Here, the latest research results increasingly point to the fact that a comprehensive implementation of device-supported procedures is unavoidable, even in the outpatient aftercare sector. The paradigm shift in neurology is not yet complete – we are in the middle of it!
Text: Jakob Tiebel
Are traditional methods still effective?Traditional physiotherapeutic schools such as Bobath, Proprioceptive Neuromuscular Facilitation or Vojta hardly differ from each other in their effectiveness. Supporters of these schools assume a transfer from one learned motor task to the next. A monocausal chain is postulated which, according to the Bobath concept, regards sitting and standing, for example, as an essential prerequisite for walking. Against the background of current findings on motor learning and functional recovery in central motor movement disorders, however, these views are hardly tenable. Despite all the criticism, however, the traditional methods still enjoy a good reputation today and sometimes determine the treatment routines, even though they hardly stand up to the increasing demand for evidence-based treatment.
Development of modern locomotion therapyFortunately, stance and gait rehabilitation has undergone a change in recent decades. In contrast to the strictly formalised therapy concepts, a task-specific repetitive approach has increasingly prevailed, in which the motor task to be learned is practised through the maximum repetition of the same task.
Modern locomotion therapy includes repetitive walking exercises even using modern gait machines and treadmills with safety belts. Where once the emphasis was on tone reduction and the practice of gait-preparation skills while seated, standing and walking are now practised in function as early as possible. Fig. 1: The Skaggs-Robinson curve is derived from the hypothesis of the same name formulated by American psychologists Ernest B. Skaggs and Edward S. Robinson to describe the effects of similarity of presented learning content on retention performance. The more similar tasks are, the greater the learning transfer between them. The more different they are, the lower the transfer of learning. Similar tasks whose requirements diverge with regard to the learning objective can even have a negative effect on learning success (negative transfer). If there is a complete deviation from the learning objective, there is no transfer (zero transfer). (Exercise pictures © by www.physiotherapyexercises.com).
Phase classification in gait rehabilitationThree essential transition phases with different objectives can be distinguished over the course of rehabilitation, according to the patient's limitations:
- Mobilisation of the patient from the bed
- Restoration of walking ability
- Improvement of endurance (walking distance), walking speed and gait stability
Robotics simplifies high?frequency therapyIf walking is practised by walking, the number of steps per training session seems to be essential for the success of the treatment, regardless of the technique used. However, the physical exertion associated with manual procedures is hardly tolerable for therapists. According to current guidelines, patients who are unable to walk should achieve 800 – 1000 steps per day. Therefore, it is always recommended to use a gait trainer to achieve the required therapy intensity. The gait trainer, with which the patient can practise walking repetitively while wearing a safety belt, does not replace the therapist. The use of a gait trainer as a supportive basis is more effective, so that according to current studies every fourth to seventh inability to walk can be avoided.
Prediction of walking ability after a strokeThe probability of being able to walk independently again after a stroke is vitally important for patients and their relatives. The ability to move independently determines the degree of independence in everyday life after rehabilitation and thus the necessary steps in hospital discharge planning. Already in the first week after a stroke, the "TWIST" algorithm can be used to make a fairly accurate prediction as to whether and how well stroke patients can walk again after six to twelve weeks of rehabilitation. All that's needed is two simple motor tests, which can be carried out by the therapist at the patient's bed.
Fig. 3: The figure shows the TWIST algorithm. Patients with a TCT score >40 in the first week after a stroke are 95% likely to walk independently again after 6 weeks. In patients with a TCT <=40, it is muscle strength in the hip extensions that is critical for the outcome after 12 weeks. Patients with a muscle strength >=3 in the first week after a stroke can walk independently after 12 weeks. The remaining patients require assistance even after 12 weeks. They are unable to walk independently. Marie-Claire Smith and her colleagues investigated numerous predictors for the recovery of walking ability after a stroke in a study conducted in 2017. Based on their analyses, they came to the conclusion that a fairly accurate prediction is possible on the basis of simple assessments (the trunk control test and the MRC hip extension force levels). The TWIST algorithm derived from the test results can support clinical decision-making and provide an outlook on the expected functional recovery (s. THERAPY 2/2018, p. 27). In addition, Mahendran and colleagues report in their 2019 publication that, in stroke patients, endurance at the time of discharge from hospital in particular can be regarded as a predictor of activity behaviour in the first 6 months (see article p. 56 in this issue).
New findings on the use of the gait trainerAccording to experts to date, treadmill training is particularly suitable for patients who are already able to walk to improve walking distance and walking speed, and electromechanically assisted walking training is particularly suitable for patients who are not able to walk to restore walking ability. The German working group headed by Jan Mehrholz and Marcus Pohl brings this into focus in its systematic review work with network meta-analysis published at the end of 2018 and produces some new findings. The evaluation included 95 randomised controlled trials with a total of 4458 patients after a stroke. Mehrholz and his colleagues state that "What is special about this network meta-analysis is that, for the first time, competing approaches to improving walking after a stroke were jointly evaluated and made statistically directly comparable, so that their effects could be assessed in a differentiated way." The work can thus be seen as a supplement to the previous Cochrane Reviews and meta-analyses. In their results section, the researchers come to the conclusion that, compared to conventional gait therapy, end-effector-assisted gait training in particular significantly and clinically improves gait speed and gait endurance after a stroke. In contrast, treadmill therapy with partial body weight relief achieves significant and clinically significant improvements in gait endurance compared to conventional therapy. Furthermore, the analyses, as well as earlier publications of this and other working groups, again point to the advantage of gait training with end effector devices compared to exoskeletal systems. However, there are still no controlled studies that directly compare the different device-specific approaches. Fig. 4: As early as 2012, Mehrholz and his colleagues reported for the first time within the framework of a systematic review with meta-analysis on the possible advantages of end effector-based gait training compared to exoskeleton and conventional gait training. The results of the network meta-analysis from 2018 underline these findings, whereby end effector systems in the continuum of gait rehabilitation offer a broad spectrum of therapy options. They can be used sensibly, from restoring walking ability to improving walking speed and gait endurance.
Clear recommendation in the direction of device supportIn practice, the results mean that electromechanically assisted gait therapy, due to its demonstrable advantages, is currently probably the best therapy option for improving the various dimensions of walking. According to Mehrholz and colleagues, the research results have significant effects on neurological rehabilitation. A comprehensive implementation of device-based therapy procedures in neurological gait rehabilitation is required. These demands have a particularly strong impact on the outpatient sector and its financing. A rethink is inevitable: away from traditional physiotherapy on a neurophysiological basis towards modern methods of device-based gait rehabilitation.
The dose brings successIn addition to the task orientation, a "dose-effect" relationship in neurological rehabilitation is assumed according to current findings in therapy science. It describes the relationship between exercise frequency, duration and intensity and the treatment result. The motto here is "more is better...". Reconcile this with the demand for task specificity and we can postulate: "...and a specific more is the best!".
Standardised measurement methods in gait rehabilitationThe Functional Ambulation Categories (FAC) are particularly suitable for determining walking ability. With their help, therapists can quickly and intuitively assess walking ability in five steps in clinical everyday life. The result is decisive when, for example, it comes to dividing patients into subgroups for gait therapy according to their ability level (see THERAPY 2, 2017 p. 16). The 6-minute walking test (6-MWT) is suitable for measuring the walking distance and endurance. Over a period of six minutes, the patient walks as quickly as possible on a flat track. A circuit that prevents abrupt changes in direction and tempo is most suitable for this. The distance travelled is measured by the therapist using a distance measuring wheel or the distance marked out. The walking speed at self-selected speed or if necessary at high speed can be determined by means of a 10-metre walking test (10-MWT). The test is also very simple. Four points are marked on level ground. The first marking is the starting point (0 m). The second marking is at 2 m. The measuring person uses this as the time measurement starting point. The third marking is at 8 m: This is where the time measurement ends. The fourth marking is the end point for the test person (10 m). A distance of 10 m is marked, but the time is only measured for a distance of 6 m. The time is measured with a stopwatch, the walking speed is measured in seconds and tenths of a second and then converted to metres/second. For balance, the Berg Balance Scale (BBS) remains the gold standard, although the BEST and other specific assessments to determine the individual fall risk should not be completely ignored. The decision for or against a measuring instrument can vary depending on the evaluation. The Functional Ambulation Categories (FAC) are particularly suitable for determining walking ability. With their help, therapists can quickly and intuitively assess walking ability in five steps in clinical everyday life. The result is decisive when, for example, it comes to dividing patients into subgroups for gait therapy according to their ability level (see THERAPY 2, 2017 p. 16). The 6-minute walking test (6-MWT) is suitable for measuring the walking distance and endurance. Over a period of six minutes, the patient walks as quickly as possible on a flat track. A circuit that prevents abrupt changes in direction and tempo is most suitable for this. The distance travelled is measured by the therapist using a distance measuring wheel or the distance marked out. The walking speed at self-selected speed or if necessary at high speed can be determined by means of a 10-metre walking test (10-MWT). The test is also very simple. Four points are marked on level ground. The first marking is the starting point (0 m). The second marking is at 2 m. The measuring person uses this as the time measurement starting point. The third marking is at 8 m: This is where the time measurement ends. The fourth marking is the end point for the test person (10 m). A distance of 10 m is marked, but the time is only measured for a distance of 6 m. The time is measured with a stopwatch, the walking speed is measured in seconds and tenths of a second and then converted to metres/second. For balance, the Berg Balance Scale (BBS) remains the gold standard, although the BEST and other specific assessments to determine the individual fall risk should not be completely ignored. The decision for or against a measuring instrument can vary depending on the evaluation.
Suggestions for further researchFuture gait rehabilitation studies should focus on the dose-effect relationship (number of repetitions) and therapy intensity. According to Mehrholz and colleagues, systematic reviews should include individual patient data in order to be able to describe the effects of gait training even more precisely. Furthermore, as already mentioned, there are still no controlled studies that directly compare the different device-specific approaches. This aspect, too, should be the subject of future research in order to back up previous findings regarding which systems provide the greatest benefit for gait rehabilitation and when. In order to answer all research questions, multicentre studies with a sufficiently large number of cases will usually be necessary. This should be seen as a challenge and not as an insurmountable hurdle and should be well considered and calculated in the preliminary planning phase.
 Berg K, Wood-Dauphinee S, Williams JI, Gayton D (1989). Measuring balance in the elderly: preliminary development of an instrument. Physiotherapy Canada 41: 304-311.
 Bohannon RW (1997). Comfortable and maximum walking speed of adults aged 20-79 years: reference values and determinants. Age Ageing;26(1): 15-9.
 Bohannon RW et al. (1996). Walking speed: reference
values and correlates for older adults. J Orthop Sports Phys Ther 1996;24(2):86-90.
 Cumming TB, Thrift AG, Collier JM, et al. (2011) Very early mobilization after stroke fast-tracks return to walking: further
results from the phase II AVERT randomized controlled trial. Stroke 42: 153-8.
 French B, Thomas LH, Coupe J et al. (2016). Repetitive task training for improving functional ability after stroke. Cochrane
Database Syst Rev 11: CD006073.
 Hesse S, Werner C (2010). Elektromechanisch gestützte Gangrehabilitation nach Schlaganfall. neuroreha 1: 10-14.
 Hummelsheim H, Mauritz KH (1993). The neurophysiological basis of exercise physical therapy in patients with central hemiparesis. Fortschr Neurol Psychiatr 61: 208-216.
 Knecht S, Hesse S, Oster P (2011). Rehabilitation after stroke. Dtsch Arztebl Int 108(36): 600-6.
 Mehrholz J, Pohl M 2012). Electromechanical-assisted gait training after stroke. A systematic review comparing endeffector and exoskeleton devices. J Rehabil Med 44: 193-9.
 Mehrholz J, Pohl M, Kugler J, et al. (2018). The improvement of walking ability following stroke – a systematic review and network meta-analysis of randomized controlled trials. Dtsch Arztebl Int 115(39): 639-45.
 Mehrholz J, Thomas S, Elsner B (2017). Treadmill training and body weight support for walking after stroke. Cochrane Database Syst Rev: CD002840.
 Mehrholz J, Thomas S, Pohl M et al. (2017). Electromechanical-assisted training for walking after stroke. Cochrane Database Syst Rev: CD006185.
 ReMoS Workgroup (2015). S2e-Guideline, Rehabilitation of Mobility after Stroke. Neurol Rehabil 21: 355-494.
 Wolf et al. (1997). Establishing the reliability and validity of measurements of walking time using the Emory Functional
Ambulation Profile. Phys Ther;79(12):1122-33.
Jakob Tiebel is occupational therapist. His experience in the medical field are based on his work in neurorehab in several years. 2012 he changed first into the field of health cares suppliers and 2013 to medica Medizintechnik GmbH. Cross-departmental projects in marketing, sales and product management are his core tasks.
He is specialised on the implementation of evidence-based robotic treatment concepts into the clinic daily life and thus significantly involved in developing therapy concepts of the company.