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NeuroRehabilitation 35 (2014) 779–788 DOI:10.3233/NRE-141173 IOS Press

Quantitative gait analysis in patients with Parkinson treated with deep brain stimulation: The effects of a robotic gait training Alice Nardoa,∗ , Federica Anasettib , Domenico Servelloc and Mauro Portac a Motion

Analysis Laboratory, IRCCS Istituto Ortopedico Galeazzi, Milano, Italia of Physical Medicine and Rehabilitation, Egarsat-SUMA, Terrassa, Barcelona, Spain c Division of Functional Neurosurgery and Tourette Center, IRCCS Istituto Ortopedico Galeazzi, Milano, Italia b Department

Abstract. BACKGROUND: Despite Deep Brain Stimulation (DBS) improves cardinal symptoms of Parkinson’s Disease (PD), its effect on walking impairment is less evident. Robotic-assisted rehabilitation systems could serve as “add-on” physical therapy for PD patients. This systems are able to anticipate and correct the trajectory of patients’ motion to improve their motor function recovery. OBJECTIVE: Aim of the present study was the quantitative assessment of the effects of a Robotic-Assisted Rehabilitation Protocol (RARP) on gait patterns by means of three-dimensional gait analysis on PD patients treated with DBS. METHODS: 9 patients with PD treated with DBS were submitted to 5 weeks robotic-assisted rehabilitation sessions. Threedimensional gait analysis was performed before the starting session, and one day after the last session using an optoelectronic system with passive markers. RESULTS: The RARP showed significant improvements on spatio-temporal gait parameters and on the Unified Parkinson’s Disease Rating Scale motor score. CONCLUSIONS: The RARP with Lokomat may have positive effects on spatio-temporal gait parameters of PD patients and it could be an adjunct therapy for patients treated with DBS. On the other hand kinematic and kinetic gait parameters did not show significant improvements, remaining almost comparable before and after the RARP. Keywords: Parkinson’s disease, gait analysis, robotic-assisted rehabilitation, deep brain stimulation, locomotor system

1. Introduction Parkinson’s disease (PD) is a neurodegenerative disorder which is mainly related to a deficiency of dopamine in the substantia nigra of the basal ganglia. This disorder impairs particularly patients motor skills and cognitive process. In PD individuals are frequently observed instability and gait impairments, typically characterized by an alteration of spatiotemporal parameters, such as reduced velocity, shorter stride length and increased stance phase (Roiz et al., 2010; Sofuwa et al., 2005; Morris, Iansek, McGinley, ∗ Address

for correspondence: Alice Nardo, Via Riccardo Galeazzi 4, 20161 Milano, Italy. Tel.: +39 02 66214009; Fax: +39 02 66214048; E-mail: [email protected].

Matyas, & Huxham, 2005). Gait cadence is usually not altered except in some cases, where it increases as adaptation to stride length reduction (Morris, Iansek, Matyas & Summers, 1994; Morris, Iansek, Matyas & Summers, 1998). Automatic 3D gait analysis techniques, showed an altered kinematic and kinetic, typified by reduced range of motion (ROM) of the lower limb joints, a flexed forward posture, lowered peaks of ground reaction forces (GRF) and a reduced peak of power production at lower limb joints (Roiz et al., 2010; Morris et al., 2005; Mirek, Rudzinska & Szczudlik, 2007; Morris, McGinley, Huxham, Collier & Iansek, 1999). Pharmacological treatment remains unsatisfactory for many patients: severe motor complications, such as motor fluctuations and dyskinesias, cause functional disability and as a consequence a strong impact on subjects’ Quality Of

1053-8135/14/$27.50 © 2014 – IOS Press and the authors. All rights reserved

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A. Nardo et al. / Quantitative gait analysis in patients with Parkinson

Life (QOL) (Bejjani et al., 2000). These patients could be considered candidates to functional neurosurgery of basal ganglia. Subthalamic nucleus (STN) deep brain stimulation (DBS) is a surgical management for PD which can reduce rigidity, akinesia and tremor, this improvement has been shown using the UPDRS motor score (Bejjani et al., 2000; Yokoyama et al., 1999). Many studies have already reported a 3D kinematic and kinetic gait analysis, demonstrating the positive effects on gait produced by DBS and/or pharmacologic therapy in PD patients (Ferrarin et al., 2005; Krystkowiak et al., 2003). Despite the remarkable advances in pharmacologic therapy and surgical procedures, PD patients still develop progressive gait disability (St George, Nutti, Burchiel, & Horak, 2010). Therefore, an “add-on” non-pharmacological and non-surgical therapy, such as physical rehabilitation, is indicated as its effectiveness has been already demonstrated (De Goede, Kleus, Kwakkel & Wagenaar, 2001; Goodwin, Richards, Taylor RS, Taylor AH, & Campbell, 2008). Indeed physiotherapy is aiming at enabling PD patients to maintain their maximum level of mobility, activity and independence, and, consequently, to improve their QOL. Currently many evidences recommend the treadmill training instead of the conventional physiotherapy for PD patients with gait hypokinesia, suggesting that this kind of training could improve patients’ walking speed and stability (Mehrholz et al., 2010). Treadmill training with body-weight support (BWS) is already used to enhance the gait of post-stroke and spinal cord injury patients (Moseley, Stark, Cameron & Pollok, 2005). Miyai et al. (2000) found that 4-week BWS treadmill training produced higher improvement of motor performances of PD patients compared with traditional physical therapy. Their results showed an increment both of stride length and of gait speed (Miyai et al., 2000). Toole et al. (2005) investigated the effects of 6 weeks of treadmill training in 3 groups of subjects with PD, trained with different amounts of weight bearing. Significant improvements were seen in all groups, irrespective of the amount of weight bearing. However, unlike in post-stroke patients, BWS is seemingly not crucial for PD patients (Pohl, Rockstroh, Ruckriem, Mrass & Mehrholz, 2003; Protas et al., 2005; Frenkel-Toledo et al., 2005). These studies suggest that a long-term treadmill walking intervention program, without BWS, would be able to rehabilitate patients’ walking rhythmicity, reduce gait variability and successfully decrease the risk of patients’ fall. That is why nowadays there is a growing interest for automatic robotic devices for gait training, proposed as

clinical tools in rehabilitation of gait-impaired individuals, in particular for patients suffering from neurological disorders. This kind of robotic devices are based on a treadmill training assisted with a robotic driven gait orthosis, which are able to anticipate and correct the trajectory of patient’s stride according to a physiological pattern. This systems furthermore provide to patients several proprioceptive inputs imposing symmetrical lower-limb trajectories which improve motor function and cortical activation while minimizing the demands on therapists (Ridgel, Vitek, & Alberts, 2009; Takahashi, Der-Yeghiaian, Le, Motiwala, & Cramer, 2008). It has been shown, in recent times, that roboticassisted treadmill training could also be applied as a therapy to specifically treat freezing of gait in patients with PD (Lo et al., 2010). The neuroplasticity of the central nervous system allows, by repeated execution of altered movements through an external assistance, a better recovery of patients’ motor function (Martino, 2004). Recently a randomized controlled trial has compared the effects of robotic gait training versus the effects of conventional gait training with a treadmill on PD patients, showing that robotic gait training is not superior to gait training on a treadmill in early-stage PD patients (Carda et al., 2012). The improvement of walking and stability are the primary goals of gait therapy in patients with PD, and nowadays robotic treatments are becoming more popular in the neurorehabilitation field, that’s why is extremely important the evaluation of their effectiveness and also of their limits. None of the reported previous studies has evaluated the PD patients walking recovery by a three-dimensional analysis of gait. Therefore the aim of the present study was the quantitative assessment of the effects of a Robotic-Assisted Rehabilitation Protocol (RARP) on gait patterns by means of three-dimensional gait analysis on PD patients treated with DBS. Kinematics and dynamics of the locomotion have been investigated before and after the experimental rehabilitation protocol as to verify the hypothesis that it could serve as an “add-on” therapy capable to improve patients’ walking patterns.

2. Materials and methods 2.1. Lokomat® The Lokomat® (Hocoma AG, Volketswil, Switzerland) is a bilateral driven gait orthosis that is used in

A. Nardo et al. / Quantitative gait analysis in patients with Parkinson

conjunction with a BWS system able to reproduce gait movements similar to normal walking, in order to generate appropriate afferent input to patient’ central nervous system. The patient is fixed to the orthosis which can be adapted to fit the individual’ anthropometry. The Lokomat® system moves the patient’ legs in the sagittal plane using robotic hip and knee joints actuated by linear drives. This drives are integrated into an exoskeletal structure which is adjustable in step length and velocity. Patient’ leg motion is controlled by predefined and highly repeatable hip and knee joint trajectories based on a conventional position control strategy. The hip and knee joint trajectories can be manually adjusted to better fit the subject’ characteristics by changing amplitude and offsets. The BWS system allows the variation of the vertical force support, in order to compensate the effect of inertia induced by the vertical movements during gait (Frey et al., 2006). Moreover, a biofeedback technology has been developed in order to motivate and engage patients increasing the benefits on motor and neurological rehabilitation (Schmidt & Wrisberg, 2000). 2.2. Patients Nine subjects with PD (7 males and 2 females; age: 66.4 ± 6.0 years; weight: 75.32 ± 18.40 kg; duration of DBS treatment: 3.11 ± 1.27 years) treated with DBS since 2 to 5 years were included in the study. Patients’ exclusion criteria were: inability to walk without walking aids or assistance; previous orthopedic surgery, cardiovascular disorders, visual disturbances or other neurological conditions that can affect subject’ walking ability. The patients included were evaluated and rehabilitated by the robotic-assisted treadmill Lokomat® (Hocoma AG, Volketswil, Switzerland). All the patients were medicated with L-Dopa (mean range 400 mg per day) and all trials were performed while the patients were ON medication and with DBS stimulation activated. A neurologist examined the patients’ functional disability level using the Unified Parkinson’s Disease Rating Scale (UPDRS) (Martinez-Martin et al., 1994) at the beginning and at the end of the rehabilitation period. Table 1 summarizes the patients’ main characteristics. 2.3. Rehabilitation protocol The patients with PD have been studied during a 5-weeks rehabilitation session with a body-weight supported and robotic-assisted treadmill, Lokomat® (Hocoma AG, Volketswil, Switzerland). All patients

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had 45 minute session of Lokomat rehabilitation every day. All participants started with a treadmill speed of 1.5 km/h and 40% of BWS. BWS was mainly used to facilitate an increase in walking speed. Therefore the training progression across subsequent sessions was arranged so as gradually increase treadmill speed and unload BWS. Speed was increased up to a range of 2.0 to 3.0 km/h, as tolerated, and adjusted during rehabilitation while BWS was gradually decreased. By the end of the 5-weeks training session, all participants were walking with 0% BWS. We defined our protocol according to our clinical experience, the Lokomat technical characteristics (speed up to 3.2 km/h), and the treadmill training protocols in the literature that suggest a progressive reduction of body weight support combined with an increase of gait speed (Miyai et al., 2000; Miyai et al., 2002). The rationale for supporting body weight was to increase patients’ safety and compliance with the RARP. 2.4. Gait analysis Gait assessment was performed one day before the first training session (PRE-RARP), and one day after the end of the rehabilitation protocol (POST-RARP) using an optoelectronic system with passive markers (EliteClinic, BTS Bioengineering, Milan, Italy). The EliteClinic system enables the computerized three-dimensional motion registration using six optoelectronic cameras working at a sample rate of 100 Hz. 22 passive markers were placed on patients’ bony landmarks in accordance with the Davis protocol (Davis, Ounpyy, Tyburski & Gage, 1994). The kinetic variables registration was performed using a dynamometric force platform (Kistler, Postfach, Switzerland). Patients were told to walk barefoot several times at natural speed within the movement area registered by the cameras. 2.5. Data analysis For each patient at least six trials for leg were collected in order to guarantee the repeatability of the results. These trials were considered for the following analysis of spatio-temporal parameters, kinematic and kinetic variables. Mean gait velocity (m s-1), cadence (steps min-1), duration of stance (as % of gait cycle) and stride length (m) were considered as spatio-temporal parameters. The kinematic parameters analyzed are related to the lower limb joints: hip, knee and ankle. In particular for hip joint the maximal flexion at initial contact phase (0–2% of gait cycle) and the maximal

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A. Nardo et al. / Quantitative gait analysis in patients with Parkinson Table 1 Patients’ clinical characteristics

Patient number

Age (years)

Sex

Disease duration (years)

#1

71

M

6

#2

65

M

25

#3 #4

55 63

M M

#5 #6

70 71

#7 #8 #9

Weight (Kg)

Height (cm)

DBS (years)

177

2

71.8

165

5

6 12

103.2 82

180 178

3 2

M M

10 17

66.6 76.8

160 170

5 4

71

M

10

58.6

162

3

72 60

F F

17 7

47.6 69.3

155 150

2 2

102

extension at terminal stance phase (30–50% of gait cycle) were computed. For knee joint the maximal flexion at initial contact phase and the maximal flexion at swing phase (60–100% of gait cycle) were computed. Finally, for ankle joint were computed the maximal dorsiflexion in the mid-stance phase (10–30% of gait cycle) and in the swing phase (60–100% of gait cycle) and the maximal ankle plantar flexion in terminal stance phase. Lastly, for each joint, the ROM on the sagittal plane was evaluated. In order to investigate the patients’ ability during the gait cycle the kinetic parameters computed are the maximal produced ankle power, the first and second peak of the GRF vector and the minimum value between them, each one normalized to the subject’s weight. 2.6. Statistical analysis After the assessment of the normality of the samples using the Shapiro-Wilk test, a paired t-test was performed to compare the spatio-temporal, kinematic and kinetic parameters before and after the RARP. A p-value of less than 0.05 was reported as statistically significant.

3. Results 3.1. UPDRS motor scores The UPDRS motor scores improved in all patients after the RARP (Fig. 1). Compared to the PRE-RARP, the POST-RARP condition has showed a decrease of

Medication levodopa/carbidopa; ropinorolo; levodopa/benserazide; bromazepam rasagilina; ropinorolo; levodopa/benserazide; sertralina levodopa/benserazide; levodopa/carbidopa levodopa/benserazide; citalopram; ropinorolo; melevodopa/carbidopa; rasagilina levodopa/carbidopa; pramipexolo levodopa/carbidopa; entacapone; rasagilina; ropinorolo levodopa/benserazide; amantadina; lorazepam levodopa/carbidopa; ropinorolo; amantadina levodopa/carbidopa/entacapone; melevodopa/carbidopa; clozapina

23.3% in motor scores (Fig. 1, a). The improvement was more marked in the motor UPDRS gait sub-score, with a decrease of 40.7% (Fig. 1, b). The UPDRS motor scores in PRE-RARP and POST-RARP conditions are reported for each patient in Table 2. 3.2. Gait analysis Spatio-temporal gait parameters, kinematic and kinetic values (as mean ± standard deviation) for all patients are reported in Table 3. After the RARP, all the spatio-temporal gait parameters significantly improved (Fig. 2). In the POST-RARP condition, patients’ mean gait velocity was significantly higher than in the PRE-RARP condition (0.77 ± 0.11 m/sec vs. 0.63 ± 0.19 m/sec, p < 0.05, Fig. 2, a). This was due to a significantly higher mean cadence (105.97 ± 11.75 steps/min vs. 95.15 ± 15.12 steps/min, p < 0.05, Fig. 2, b) and a significantly higher stride length (0.87 ± 0.11 m vs. 0.79 ± 0.20 m, p < 0.05, Fig. 2, c). The decrease of the stance timing, as percentage of the gait cycle, was also significant in the comparison between the two conditions (62.03 ± 5.69 % vs. 64.14 ± 3.17 %, p < 0.05, Fig. 2, d). Regarding the kinematics parameters, statistical significant results were found only concerning patients’ ankle joint. The comparison showed a greater maximal ankle plantar flexion angle (negative values) in the toe-off phase (−3.18 ± 6.92 degrees vs. −0.69 ± 5.96 degrees, p < 0.05) which leads to a consequent significantly greater ankle ROM (14.26 ± 4.58 degrees vs. 12.97 ± 4.83 degrees, p < 0.05) for patients in the POST-RARP condition, approaching that of the normal

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Fig. 1. UPDRS motor score and sub-score of gait in PRE-RARP and POST-RARP conditions; (a): UPDRS motor scores for all patients with PD; (b): averaged UPDRS sub-score of gait; (∗ ): significant difference (p < 0.05) in POST-RARP compared to PRE-RARP values. Table 2 UPDRS motor scores and motor sub-score of gait in PRE-RARP and POST-RARP conditions for each patient Patient number #1 #2 #3 #4 #5 #6 #7 #8 #9 Mean±S.D.

UPDRS III Score (0 – 176)

Gait score (0 – 4)

PRE-RARP

POST-RARP

PRE-RARP

POST-RARP

33 42 34 36 23 40 42 44 36 36.7 ± 6.4

24 33 26 29 17 32 30 34 28 28.1 ± 5.3

2 3 3 3 2 3 2 3 3 2.7 ± 0.5

1 1 2 2 2 1 1 2 2 1.6 ± 0.5

reference value for both parameters. Statistical analysis showed a not significant effect of the Lokomat rehabilitation for hip and knee kinematic parameters. For the hip joint, the ROM during gait was similar in PRE and in POST-RARP and this was due to an increased hip extension after the rehabilitation and at the same time to a reduced hip flexion. The maximal hip extension slightly improved in the POST-RARP condition but still remaining far from the normal reference value. This is probably due to the forward trunk lean and to the flexed knees typical of the PD posture. The trunk lean showed an inhibition of the hip extension in particular in the terminal stance phase. The mean values of knee maximal flexion both at initial contact phase and at swing phase were still lower than that of the normality in POST-RARP conditions. Statistical analysis showed a not significant effect of the Lokomat rehabilitation on the kinetic variables. However, a slight increase of the ankle power in the

terminal stance was found (Fig. 3, a). In the POSTRARP condition, the pattern of the kinetic variables showed a reduction of the absorbed ankle power in the initial stance phase and a slight increase of the produced ankle power in the terminal stance phase (Fig. 3, a). First and second peaks of the GRF were similar in POSTRARP compared to PRE-RARP condition. The average maximal values of the vertical ground reaction force (Fig. 3, b) both in the initial and in the terminal stance phases remain lower than the normal reference value.

4. Discussion The aim of the present study was the quantitative three-dimensional assessment of gait as effect of a RARP on PD patients surgically treated with DBS. The study examined the possibility that this kind of rehabilitation protocol could represent an adjunct physical

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Table 3 Spatio-temporal, kinematic and kinetic gait parameters in the PRE-LOK conditions compared to POST-RARP conditions, gait parameters of an Healthy Population (HP) are reported.; (∗ ): significant difference (p < 0.05) in POST-RARP compared to PRE-RARP values Gait parameters (mean ± s.d.) PRE – RARP Kinematic parameters Max ANKLE plantar flexion (deg) −0.69 ± 5.96 Max ANKLE stance dorsiflexion (deg) 12.28 ± 4.69 Max ANKLE swing dorsiflexion (deg) 5.15 ± 5.59 ANKLE ROM (deg) 12.97 ± 4.83 Max KNEE initial contact flexion (deg) 20.50 ± 9.07 Max KNEE swing flexion (deg) 49.65 ± 7.61 KNEE ROM (deg) 42.05 ± 6.86 Max HIP flexion (deg) 33.90 ± 6.43 Max HIP extension (deg) 0.69 ± 11.63 HIP ROM (deg) 33.22 ± 8.16 Kinetic parameters and Ground Reaction Forces (GRF) I GRF peak (% body weight) 101.77 ± 7.35 II GRF peak (% body weight) 100.13 ± 4.72 Max ankle power generated (W/Kg) 1.27 ± 0.53 Spatio-temporal parameters Stance phase duration (% of gait cycle) 64.14 ± 3.17 Stride length (m) 0.79 ± 0.20 Mean gait velocity (m/s) 0.63 ± 0.19 Frequency (steps/min) 95.15 ± 15.12

POST - RARP

HP

PRE-RARP VS POST-RARP(P value)

−3.18 ± 6.92 11.08 ± 4.95 3.52 ± 5.57 14.26 ± 4.58 18.23 ± 8.20 48.43 ± 8.58 42.59 ± 5.50 30.43 ± 6.05 −4.19 ± 8.00 34.62 ± 6.12

−11.6 ± 2.9 15.1 ± 1.1 5.5 ± 1.8 26.7 ± 1.8 14.6 ± 0.3 59.9 ± 1.2 58.8 ± 0.1 29.5 ± 1.2 −12.3 ± 0.8 41.8 ± 0.4

P = 0.046∗ P = 0.356 P = 0.166 P = 0.038∗ P = 0.355 P = 0.565 P = 0.597 P = 0.093 P = 0.059 P = 0.139

101.20 ± 6.64 98.98 ± 4.24 1.59 ± 0.50

106.3 ± 1.2 112.2 ± 1.9 3.72 ± 0.04

P = 0.687 P = 0.348 P = 0.150

62.03 ± 5.69 0.87 ± 0.11 0.77 ± 0.11 105.97 ± 11.75

59.6 ± 1.2 1.4 ± 0.07 1.33 ± 0.06 113.8 ± 4.3

P = 0.020∗ P < 0.001∗ P < 0.001∗ P < 0.001∗

treatment able to significantly improve gait patterns of PD patients treated with DBS. We focused on this issue because PD is a motor disorder that impacts on QOL: even after DBS therapy PD patients still develop progressive motor disability (Picelli et al., 2012). The results showed that a 5-weeks rehabilitation session of robotic-assisted treadmill training with Lokomat may improve gait performance on PD patients treated with DBS, in particular concerning spatio-temporal gait parameters and ankle joint ROM. Significant improvements can be observed after the Lokomat rehabilitation in mean gait velocity and cadence, in stride length and in stance phase duration. The improvement of gait speed, promoted by the rehabilitation sessions, mainly results from stride length and ankle plantar flexion changes. In this sense we inferred that the RARP could enforce the process of gait pattern generation of patients with PD. From a rehabilitative point of view this could be of great interest, because gait speed is the main independent contributor to PD walking ability. It is clear the positive effect of Lokomat rehabilitation also on UPDRS motor score as well as gait sub-score. On the other hand we should underscore that kinematic and kinetic gait parameters did not show significant improvements, remaining almost comparable before and after the RARP with Lokomat, still far from the HP values. Abnormalities in the kinetic patterns are typically pronounced in subjects with PD (Sofuwa et al.,

2005) compared with that of the healthy population. In particular concerning the ankle joint: an altered pattern of ankle plantarflexion is related to a reduced ankle power generated during the push off phase (Sofuwa et al., 2005). Our study results are consistent with the recent randomized controlled trial conducted by Picelli et al. (2012) which has investigated the robotic-assisted gait training performances comparing them with that of the traditional rehabilitation program in PD patients. Their findings demonstrated that the robotic-assisted gait training was more effective in improving walking ability than the conventional physiotherapy for PD patients. Similarly Lo et al. (2010) demonstrated the efficacy of repetitive robotic-assisted treadmill training on improving gait while reducing “freezing of gait” episodes in PD patients. They submitted PD patients to Lokomat twice weekly, for 5 weeks, in order to obtain an intense stereotyped gait training to reinforce gait automaticity and thus to reduce freezing. Robotic training could enhance the automating of motor control by stimulating the central pattern generation through a greater activation of hip extensors as compared with the proprioceptive neuromuscular facilitation (Picelli et al., 2012). On the other hands also the sole treadmill training has been shown to have beneficial effects both motor and non-motor aspects of QOL in subjects with PD (Herman, Giladi, Gruendlinger, & Hausdorff,

A. Nardo et al. / Quantitative gait analysis in patients with Parkinson

785

Fig. 2. Spatio-temporal gait parameters: spatio-temporal gait parameters for PD patients in the PRE-RARP and POST-RARP conditions; (a): mean velocity (m/sec); (b): cadence (step/min); (c): stride length (m); (d): stance duration (% gait cycle); (∗ ): significant difference (p < 0.05) in POST-RARP compared with PRE-RARP values; Healthy Population (HP) reference values are reported for each parameter.

2007). Herman et al. (2007) confirmed the effectiveness of a 6 weeks intensive treadmill training on gait and QOL of PD patients, suggesting that this kind of training program can be used to minimize gait impairments, reduce fall risk and consequently increase QOL in this patients. Other previous studies (Miyai et al., 2000; Phol et al., 2003; Protas et al., 2005; Filippin, da Costa, & Mattioli, 2010) suggest that treadmill training is more effective than conventional approaches to improve gait characteristics associated with PD. The challenging question is than whether the roboticassisted treadmill training can be superior to the classical treadmill training in PD patients treated with DBS. In this sense Toole et al.(Toole T) confirmed that treadmill training was effective in PD patients but they also demonstrated that BWS is not critical for

these patients, as it was reported in previous studies (Pohl et al., 2003). In this regard Carda et al. (2012) have compared in a randomized controlled trial the effects of robotic gait training versus the effects of conventional treadmill training on PD patients’ walking ability. Their results did not uphold the hypothesis that robotic gait training is superior to treadmill gait training in patients with early-stage PD. The two training procedures resulted comparable as both treatments significantly improved the walking performance of PD patients (Carda et al., 2012). To our knowledge, all the previous studies that have assessed the treadmill training effects on QOL and on motor performance in PD (Miyai et al., 2000; Phol et al., 2003; Frenkel-Toledo et al., 2005; Filippin, da Costa, & Mattioli, 2010) concerned subjects with only pharmacological therapy and not surgically

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Fig. 3. Kinetic gait parameters: averaged patterns of the ankle power (a) and of the vertical ground reaction vector (b) in the PRE-RARP and POST-RARP conditions; HP reference patterns are reported for each parameter. All patterns are plotted as mean and standard deviation.

treated. Furthermore, none of these studies include an assessment of the rehabilitation effect on gait performance by quantitative gait analysis. The present findings indicate that even after DBS treatment PD patients could develop disability in gait, and thus that an adjunct physical therapy is recommended. The RARP with Lokomat may promote a more stable walking pattern related to an increased walking speed, in patients with PD treated with DBS. However the study has a number of limitations.

This was a pilot study aimed to gather preliminary results with rather few participants. The main limitation of this study is the lack of a comparison between the RARP and a conventional treadmill gait training protocol by means of quantitative gait analysis on PD patients treated with DBS. The effects of the RARP were not tested in the long term, during which they might not be maintained. Further research would evaluate whether the RARP is of long-term benefit for these patients. Another limitation

A. Nardo et al. / Quantitative gait analysis in patients with Parkinson

of the present study is that the RARP and the DBS were combined with not uniformed pharmacological therapies. The effects of different prescription, dosage, frequency and intensity on the gait performance should also be evaluated in following studies. Another important limitation is the duration of the rehabilitation period. 5 weeks was not always tolerated by PD patients neither in inpatient nor in outpatient treatment. For these reasons, 5 patients initially recruited did not complete the protocol.

[3]

[4]

[5]

[6]

5. Conclusions [7]

These study results show that the RARP with Lokomat may have a positive effect on gait performance improvement of PD patients and that it could be an adjunct therapy on patients treated with DBS able to enhance their Quality of Life. The results support the hypothesis that patients with PD benefit from a treadmill gait rehabilitation in terms of walking ability and demonstrate the future need for the introduction of adjunct treatment able to enhance gait performance and stability in PD patients treated with DBS. Robotic-assisted treadmill training need further investigation to assessed whether or not their effect are substantial for this kind of neurodegenerative disease compared to the conventional treadmill training.

Declaration of interest

[8]

[9]

[10]

[11]

[12]

None of the Authors have proprietary, financial, professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the present manuscript. None were declared related to the sources of funding.

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Quantitative gait analysis in patients with Parkinson treated with deep brain stimulation: the effects of a robotic gait training.

Despite Deep Brain Stimulation (DBS) improves cardinal symptoms of Parkinson's Disease (PD), its effect on walking impairment is less evident. Robotic...
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