Measurement and assessment method about walking motion using wearable sensor and deep learning

Measurement and assessment method about walking motion using wearable sensor and deep learning - Measurement and assessment method about walking motion using wearable sensor and deep learning

Status

Active, not recruiting

Phases

Unknown

Study type

Interventional

Source

JPRN

Registry ID

JPRN-UMIN000055756

Enrollment

Registered

2024-10-06

Start date

2024-10-15

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

elderly, handicapped person in ambulation, prosthetic legged person

Interventions

Subjects&#39

walking motion are measured with motion capture system and movies are taken.

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Male and Female elderly people older than 65 years who can do walking motion with both legs. Male and Female elderly people older than 65 years who can do walking motion with both legs and will get surgical operation of total knee arthroplasty (TKA)/ total knee replacement (TKR)/ total hip arthroplasty (THA)/ total hip replacement (THR). In the case of prosthetic legged, a person who have a prosthetic devices on his/her single leg.

Exclusion criteria

Exclusion criteria: A person who cannot walk with his/her both legs. In the case of prosthetic legged, a person who have prosthetic devices on both legs.

Design outcomes

Primary

Measure	Time frame
Joint angle during walking motion, Optimal sensor set	—

Countries

Japan

Contacts

Public ContactJAEHOON LEE

Ehime University Graduate School of Science and Engineering

jhlee@ehime-u.ac.jp0899279709

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Jul 3, 2026