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Effect of Foot Insole on Body Alignment, and in Stroke Patients

U

University of Sharjah

Status

Enrolling

Conditions

Stroke

Treatments

Device: Customized insole

Study type

Interventional

Funder types

Other

Identifiers

NCT06756256
WonkwangUoS

Details and patient eligibility

About

Goal: This study will be conducted to find out the effects of customized insole on foot alignment, body alignment, and balance ability of stroke patients.

Recruitment: Total 20 participants will be recruited and will be divided into 2 groups: Intervention and control group with or without wearing foot insole for 6 weeks.

Evaluation tool:

  1. MediACE Scanner-MS320F will be used to evaluate foot alignment and will create customized insole.
  2. Exbody 770 will be used to measure body alignment.
  3. Timed up & go test will be used to evaluate dynamic balance.

Intervention: The intervention group will wear a customized insole during daily life for 6 weeks whereas the control group will not.

Evaluation will be conducted 2 times before and after 6 weeks.

Full description

This study will recruit 20 stroke patients and will randomly assign them to the intervention group (n=10) and control group (n=10). After given the full description of the study, participants who will voluntarily agreed to participate will be included.

This study involves producing customized insoles for participants to wear during daily activities for six weeks. The customized insoles will be produced using the MediAce Scanner-MS320F, which scans the participants' feet in a seated position.

The participants in the intervention group will wear the produced insoles during daily activities. Their rehabilitation program will be continued apart from the insole wearing.

The participants in the control group will wear their normal insoles during daily activities. Also, their rehabilitation program will be continues as same as the intervention group.

Outcome measure will be conducted twice, pre- and post-intervention. It includes foot alignments and arch height using the MediACE Scanner-MS320F, body alignments using the Exbody 770, and balance ability using the Timed Up & Go test.

Enrollment

20 estimated patients

Sex

All

Ages

50+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Chronic (more than 1 year ago) stroke patient over 50 years old
  • MMSE (mini-mental state examination) score of 24 or higher out of 30, capable of understanding the experimenter's instructions
  • No history of orthopedic surgery
  • Voluntarily agreed to participate

Exclusion criteria

  • Neurological problems other than stroke affecting balance ability
  • Movement restrictions or involuntary limb movements due to ankle pain
  • Severe visual impairment, field defects, cognitive impairment making it impossible to use evaluation equipment
  • Taking medication affecting posture and balance ability

Trial design

Primary purpose

Treatment

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

Double Blind

20 participants in 2 patient groups

3D Insole
Experimental group
Description:
Intervention group who will wear the customized insole for 6 weeks during daily activities. Insole production will be through the following process. The participants' feet will be visually inspected for abnormalities, and the MediAce Scanner-MS320F will scan the feet in a seated position with the knees and ankles fixed at 90°. MediAce Scanner-MS320F's software will automatically calculate and correct the anatomical position of bones and joints. The corrected models will produce the printed insoles. Apart from wearing insole, they will receive the physiotherapy treatment as their continuation of rehabilitation program.
Treatment:
Device: Customized insole
Control_without 3D Insole
No Intervention group
Description:
Participants in the control group will not wear the customized insoles for 6 weeks. They will receive the physiotherapy treatment as their continuation of rehabilitation program.

Trial contacts and locations

1

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Central trial contact

Juhyun Kim, PhD; Meeyoung Kim, PhD

Data sourced from clinicaltrials.gov

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