Authors: Cristina Reynders-Frederix1, Peter Reynders-Frederix2, Innocenti Bernardo3, Tamas Illes4,5, Mihai Berteanu6
1University Hospitals Brussels, campus Saint-Pierre, Université Libre de Bruxelles
2University Hospitals Brussels, campus Brugmann, Université Libre de Bruxelles
3BEAMS (Bio Electro and Mechanical Systems), Université Libre de Bruxelles
4University Hospitals Brussels, campus Brugmann, Department of Orthopedic Surgery, Université Libre de Bruxelles
5University of South Denmark, Department of Orthopedics & Traumatology, Odense
6Department of Revalidation & Physiotherapy, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
Background. Walking aids are often prescribed in the aftermath of an orthopedic condition of the lower limbs to ensure balance and reduce loading of the injured limb. Correct use of these crutches is difficult because efficient instruments are lacking to monitor the forces acting on the lower limb and crutches.
Aims. The aim of this project was to produce an atraumatic, cheap, and portable tool to assist patients and therapists in rehabilitation, and in conducting gait analysis. With the development of these instrumented crutches, the authors hope to increase their possibilities to monitor the functional evolution of a person during recovery after musculoskeletal ailments.
Methods. We describe the development of a wireless instrumented forearm crutch to monitor the gait of eighteen orthopedic patients during their convalescence. Seven volunteers served as a control group. By using four strain gauges installed as a full Wheatstone bridge, pure compression in the crutch bar is measured. A tri-axial accelerometer is used for determining the movement speed of the crutch in the sagittal plane. The pitch and roll angles in the frontal plane were measured using a tri-axial accelerometer and gyroscope.
Results. Unfortunately, no difference was found between a control group of healthy volunteers and the group of orthopedic patients. Also, the authors did not find a relation between the different gait parameters.
Conclusions. Using the three parameters obtained from the wireless connected forearm crutch, we could not create an algorithm to characterize gait in a group of patients with different orthopedic conditions of the lower leg. The results were not different from the parameters obtained from a group of healthy volunteers.
Key words: rehabilitation, partial weight bearing, strain gauges, instrumented crutches, real time monitoring, end user program, compression, full Wheatstone bridge.