FORCE MEASUREMENT DURING GAIT THERAPY

ASSISTED BY A ROBOTIC TREADMILL

The Case of Lokomat®

M. Bocciolone, M. Lurati, M. Vanali

Department of Mechanical Engineering, Politecnico di Milano, Via La Masa 34, Milano, Italy

F. Molteni

Valduce Hospital, Villa Beretta Rehabilitation Center, Via N. Sauro 17, Costamasnaga (LC), Italy

Keywords: Gait analysis, assisted gait, rehabilitation, force measurement, data analysis, controlled orthosis.

Abstract: The present paper deals with force measurement during gait therapy assisted by a special robotic treadmill

with driven robotic orthoses that guide inferior limbs movements. The objectives, the measurement setup

and the results are presented. This work has been carried out in order to gather data necessary to begin the

analysis and the design of a new ankle motion device. The presented results also show how these

measurements can be useful in gait parameters assessment and patient’s muscle activity level.

1 INTRODUCTION

Nowadays mechanical measurements give a valid

and important aid in the rehabilitation field, both for

the design of specific devices and for the

development of suitable data analysis techniques.

Different types of sensors can be fixed on the

rehabilitation machines (Comolli et al., 2005), and

particular wearable sensors allow to perform the

measurements directly on the patient’s body, e.g. the

acceleration of body segments during gait (Zijlstra,

2003). Mechanical measurements can be useful to

properly set-up the rehabilitation device parameters

or to evaluate the patient’s conditions during

rehabilitation sessions (Melis et al., 1999).

This paper deals with force measurements

applied to the case of locomotion therapy assisted by

a specific robotic treadmill, the Lokomat®. This is a

rehabilitation device composed of a driven robotic

gait orthosis that guides the patient’s legs on a

treadmill while a desired percentage of the body

weight is sustained by a special support system. The

patient is sustained while his hips, thighs, knees and

legs are actively guided during the entire gait cycle,

therefore reproducing a physiologic movement. The

feet are instead passively pulled with a spring-belt

system: consequently ankles and feet follow non

“natural” trajectories and do not reproduce the actual

human walking. The foot sustainment is strictly

necessary to avoid the patient to stumble. Even if

this eventuality wouldn’t represent a danger for the

patient’s health because of the presence of suitable

security devices, it would cause the system

emergency stop to avoid the patient to fall, thus

interrupting the rehabilitation session. The growing

interest around this topic and the study of possible

solutions are the starting point of the present work.

The internal forces exchanged between the patient

and the Lokomat® have been measured in order to

analyze the mechanical behaviour of the utter system

(human and mechanical), and to investigate the

forces transmission from the suspension system to

the ground and vice versa. This knowledge is the

basis to upgrade the ankle motion system allowing a

better control and a more physiological ankle

movement. This paper describes the design of the

tests, the experimental set-up and the obtained

results. The analysis of the results has allowed to get

information about the patient’s working conditions.

The achieved data have also been the inputs in order

to design an innovative prototype device able to

control the ankle motion (Bucca et al., 2008). The

possibility of the patient’s conditions evaluation and

the rehabilitation parameters assessment have been

therefore investigated in the paper.

Bocciolone M., Lurati M., Vanali M. and Molteni F. (2008).

FORCE MEASUREMENT DURING GAIT THERAPY ASSISTED BY A ROBOTIC TREADMILL - The Case of Lokomat

 .

In Proceedings of the First International Conference on Biomedical Electronics and Devices, pages 35-40

DOI: 10.5220/0001047400350040

 SciTePress

Force measurements during patients’

rehabilitation sessions have been performed using

suitable transducers (load cells) expressly built and

calibrated. These have been installed between the

patient and the Lokomat® frame. The body weight

sustaining force and the left/right foot pulling force

have been measured during the assisted gait, both for

an healthy subject and for an actual patient.

2 MEASUREMENT SETUP

This paragraph describes in detail the measurement

setup, the installed sensors and the Lokomat®

system.

The Lokomat® rehabilitation device (Figure 1)

is essentially composed by three parts:

1. a hip support system that sustains a desired

percentage of the patient’s weight;

2. two electrically driven leg orthoses;

3. a passive spring-belt system that pulls and

drives the feet.

Figure 1: view of Lokomat® (with the courtesy of

Hokoma, from website www.hocoma.ch).

The body weight support system allows the therapist

to set the counterweight that sustains the patient

during the gait, accordingly to the medical

directions. This parameter setup is crucial because it

influences the rehabilitation session effectiveness

and therefore the patient’s progresses. During the

gait the patient is submitted to dynamic forces,

which have been measured and analyzed using

suitable techniques. In order to perform this goal, a

specific load cell (diameter 90 mm, thickness 5 mm,

depth 30 mm, output sensitivity 7.69 mV/N) has

been installed between the cable and the pin that pull

the system frame (Figure 2). In the following it will

be referred as the sensor N. 5.

Because of the main interest toward the feet pulling

system, other transducers have been installed to

measure the involved internal forces. Four load cells

(diameter 45 mm, thickness 2 mm, depth 20 mm,

sensitivity 20 mV/N), have been inserted between

the springs and the belts that pull up the feet. Sensor

N. “1” and “2” have been installed on the left side,

“3” and “4” on the right one (Figure 3).

All the load cells are not commercial products

but have been designed and realized for this specific

application. The transducers incorporate an

aluminium cell ring as the elastic element. Four

strain gauges, located as shown in Figure 4, are used

as sensors able to measure the strains due to the

force (extension or compression) acting along a

diameter.

Figure 2: sensor number

Figure 3: sensors number

1-2 (left leg), 3-4 (right

leg).

The strain gauges are connected in a full Wheatstone

Bridge. The arrangement allows the thermal

compensation. The bandwidth is 0-20 Hz.

Figure 4: mechanical and electrical design of the load

cells.

All the output voltage signals have been acquired

with a National Instruments Acquisition System,

using a 12 bit PCMCIA DAQ card and a notebook

for data storing.

BIODEVICES 2008 - International Conference on Biomedical Electronics and Devices

3 TEST DESCRIPTION

Several tests have been carried out in two different

conditions:

1. during the gait of a 65 kg healthy person, with

no specific pathology (it will be referred as the

“normal” condition);

2. during the gait of a patient with a specific

motor disability.

In the first case (healthy subject) different speed

and counterweight conditions have been tested, and

are listed below:

• gait speed of 1.5 km/h and 2 km/h;

• counterweight of 20 kg and 35 kg;

• active and passive gait: in the active session

the subject was asked to walk in normal

conditions, therefore using his muscles at

100% and contrasting the Lokomat®

resistance; in the passive session he was asked

not to use his muscles, being completely

transported and guided by the Lokomat®

orthoses.

In the second case (real injury condition) a Spinal

Cord Injury (SCI) patient has been monitored during

a usual rehabilitation session. Because of the

specific pathology he was almost unable to use the

left leg but not the right one. Considering that the

patient used to have his gait sessions at 2 km/h with

40 kg of counterweight, two different speed

parameters have been tested (1.5 km/h and 2 km/h),

and he was asked to walk both passively and

actively. In order to prevent negative effects on the

patient’s rehabilitation sessions, only the usual 40 kg

counterweight has been tested.

4 RESULTS

This paragraph presents the results obtained in the

most meaningful tests for both test conditions.

4.1 “Normal” Conditions

A first effective analysis can be performed analyzing

the data obtained from the sensor N. 5 (the one

measuring the body sustaining dynamic force).

Figure 5 shows the force time histories 30 s long,

measured in the following conditions:

a) subject standing and suspended;

b) subject walking suspended;

c) subject walking leant with 35 kg

counterweight;

d) subject walking with 20 kg counterweight.

The measured forces, except obviously the case of

standing subject (a), present a periodic shape due to

the alternate left and right foot contact.

Figure 5: measured body sustaining force in different test

conditions.

A characteristic force waveform can be observed in

a step cycle, considering for example a 10 s long

time interval, in the case of subject walking at

1.5 km/h with a counterweight of 35 kg (Figure 6).

Figure 6: body sustaining force - time history.

The subject has a left (or indifferently right) foot

contact in 2.7 s and therefore a foot contact in 1.35 s.

The lowest force values are exhibited at the foot

contact instant while the highest when the foot rises.

The time-history analysis allows to evaluate the

actual load variations. In this case the measured

mean value is 359 N, with minimum and maximum

values equal to 310 N and 400 N. It has therefore

been calculated that the subject has sustained an

FORCE MEASUREMENT DURING GAIT THERAPY - The Case of Lokomat®

average weight of 275 N (∼28 kg), with a minimum

of 235 N (∼24 kg) and a maximum of 324 N

(∼33 kg). The analysis in the frequency domain

(using DFT techniques) is useful to identify the

dynamic component parameters. Figure 7 shows the

force amplitude spectrum: there is a main

component at 0.7 Hz (correspondent to the feet

contact frequency at a speed of 1.5 km/h) and other

lower multiple components.

Figure 7: body sustaining force - amplitude spectrum.

Table 1 contains the numeric results for all test

conditions, in terms of mean, max and min values

and peak to peak amplitude.

Table 1: measured body sustaining force (mean, max, min,

peak-to-peak values) for 35 kg and 20 kg counterweight.

35 kg 20 kg

Mean value

359 N 242 N

Max value

400 N 265 N

Min value

310 N 215 N

Peak-to-peak

90 N 50 N

The analysis of the data acquired by the cells

installed over the feet (sensors N.1 to N.4), gives

some important indications about the subject’s real

activity during the gait. Table 2 presents the numeric

results, comparing the suspended and the leant

subject conditions, both for left and right leg.

Table 2: numerical results for left/right foot pulling force.

Suspended

patient

Leant patient

Right Left Right Left

Peak-to-

peak

30 N 25 N 105 N 110

Figure 8: left and right foot pulling force (comparison

between active and passive zones).

In this case the mean values are not meaningful

because of their dependence on the static tension the

therapist gives preparing the patient. The dynamic

components are instead indices of the subject’s

muscle activity. The peak-to-peak value grows from

30 N to 105 N for the right leg and from 25 N to

110 N for the right, showing a strong increment of

the forces needed to sustain the feet when the subject

walks leant on the treadmill respect to the suspended

case.

The comparison between the time histories of the

active and passive sessions shows a significant

difference in the measured forces, being useful for

the subject’s work evaluation (Figure 8).

4.2 SCI Patient Gait

The previous analyses, performed in the case of an

healthy subject, have been applied to the case of a

SCI patient. The considered patient is affected by an

asymmetric left/right motor disability, and therefore

well suits a study case.

Figure 9: time history (body sustaining force).

passive active passive

BIODEVICES 2008 - International Conference on Biomedical Electronics and Devices

Figure 10: spectral analysis (body sustaining force).

The body sustaining force time history (Figure 9)

shows a more regular signal waveform, confirmed

by the spectral analysis (Figure 10), where the main

spectral component (associated to the foot contact

frequency) is more marked if compared with the

normal case. Comparing the active and passive

session spectra, it can be observed that the secondary

dynamic components tend to become lower in the

passive case, but when the patient tries to walk

actively a little increase appears (like the “normal”

gait case, where multiple components are well

marked).The analysis in the time domain has pointed

out significant differences in the measured

sustaining force depending on the patient’s speed

gait: the mean, max and min values of the aliquot

part of the weight sustained by the patient himself

are respectively 147 N, 59 N, 226 N for speed of 2

km/h. In the case of speed of 1.5 km/h the values are

127 N, 29 N, 226 N. The first case (2 km/h) is the

usual rehabilitation condition for the patient: he

seems therefore able to realize a more fluent gait

supporting a higher load.

The analyses of the time histories of the feet

sensors are useful to obtain indications about the

patient’s muscular activity (Figure 11).

Figure 11: left and right foot pulling force (comparison

between active and passive zones).

The calculation of the standard deviation of the

forces, index of the dynamic forces exchanged

between the patient and the orthosis, shows an

increment related to the patient gait efficiency

(Table 3, Table 4).

Table 3: feet pulling force values for 2 km/h speed.

2 km/h

Passive Active Increment

Right

12.3 N 19.8 N +61%

Left

12.6 N 14.1 N +12 %

Table 4: feet pulling force values for 1.5 km/h speed.

1.5 km/h

Passive Active Increment

Right

12.1 N 19.9 N +64%

Left

12.8 N 16.3 N +27 %

In agreement with the patient’s pathology the results

has pointed out a significant difference between

active and passive sessions only for the right leg,

with an increment of 61% and 64% respectively for

2 and 1.5 km/h, while 12% and 27% for the left leg.

5 DISCUSSIONS AND

CONCLUSIONS

Measurement chains able to gather the forces during

gait therapy assisted by a robotic treadmill have

been designed and settled-up. Results have pointed

out that these measurements can help doctors and

therapists in the patient’s assessment and the

rehabilitation parameters set-up. The obtained

results have also been the starting point for the study

of an ankle motion system improvement.

The actual load sustained by the patient during

assisted gait is a fundamental parameter. The proper

value is different for each patient, depending on the

physical condition and the specific pathology. A too

high value may be detrimental to the patient, while a

too low value may be inappropriate, raising the

patient’s recovery time length. The measurement of

the actual load, and especially of the dynamic load

variations, for sure very important to this aim, has

been performed and the results analyzed.

Beside this, the knowledge of the involved

internal forces can help the therapist in the

rehabilitation session evaluation, allowing to

properly set-up all the parameters, as the gait speed

and the session time length.

The very good results obtained in the present

work provide the basis for future developments

aimed to the real diagnostic possibilities. Additional

experimental tests will be carried out in order to

active passive active

FORCE MEASUREMENT DURING GAIT THERAPY - The Case of Lokomat®

consider a greater number of patiens, thus validating

the obtained results and estimating the associated

uncertainty levels.

The authors think that the measured internal

forces are associated to the actual muscular activity

of the patient. Therefore the next step in this

research field will be the correlation between the

measured forces and the results coming from the

electromyography of lower-limb muscles during

walking, in order to validate the presented results.

The possibility of the patient’s assessment based on

force measurements is very interesting, giving a lot

of advantages as low cost and ease of carrying out.

ACKNOWLEDGEMENTS

Authors wish to thank Mauro Rossini (Villa Beretta

Rehabilitation Centre) for his helpful discussion.

This work was supported by the Fondazione Cariplo

in the framework of the research program

HINT@Lecco.

REFERENCES

Zijlstra, W., 2003. Assessment of spatio-temporal gait

parameters from trunk accelerations during human

walking, Gait and Posture Vol. 18, 1-10.

Bucca, G., Bezzolato, A., Bruni, S., Molteni, F., 2008. A

mechatronic device for the rehabilitation of ankle

motion, BIODEVICES 2008 Conference, Funchal,

Madeira.

Comolli, L., et al, 2005. Metrological characterization of a

cycle-ergometer, 6th Congress of the Italian Society of

Movement Analysis in Clinics.

Melis, E.H., et al, 1999. Analysis of assisted-gait

characteristics in persons with incomplete spinal cord

injury, Spinal Cord, Vol. 37, Issue 6 pp. 430-439.

BIODEVICES 2008 - International Conference on Biomedical Electronics and Devices