Integrating control and feedback into a trans-femoral prosthesis

Integrating control and feedback into a trans-femoral prosthesis - Integrating control and feedback into a trans-femoral prosthesis

Status

Active, not recruiting

Phases

Unknown

Study type

Interventional

Source

NL-OMON

Registry ID

NL-OMON34125

Enrollment

Registered

2010-07-12

Start date

2010-11-14

Completion date

Unknown

Last updated

2024-05-06

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

Conditions

(bovenbeen) amputaties missing upper leg trans-femoral amputation

Interventions

For the EMG measurements the subjects will receive EMG electrodes on several muscles and they will be asked to perform activities of daily life (ADL). For the feedback experiments the subjects will

Eligibility

Age

18 Years to 99 Years

Inclusion criteria

Inclusion criteria: Healthy: no lower extrimity disorders Trans-femoral amputees: can walk by themself with prosthesis

Exclusion criteria

Exclusion criteria: Healthy: neurodegenerative diseases, skin conditions legs, mental illnesses Trans-femoral amputees: skin conditions stump, neurodegenerative diseases, mental illnesses

Design outcomes

Primary

Measure	Time frame
: Firstly, EMG measurements are used to design an algorithm which can detect the intention of the subject and timings of certain events during ADL (e,g, push-off during walking) to control a prosthesis. The algorithm is then tested and improved using healthy subjects and TFA. Secondly, feedback experiments will provide us with a method of giving feedback to the subject on the state of the prosthesis without conscious attention of the subject. Finally the optimalized EMG algorithm will be combined with the best functioning feedback modality to form a controlled TFP.	—

Measure

Time frame

: Firstly, EMG measurements are used to design an algorithm which can detect the intention of the subject and timings of certain events during ADL (e,g, push-off during walking) to control a prosthesis. The algorithm is then tested and improved using healthy subjects and TFA. Secondly, feedback experiments will provide us with a method of giving feedback to the subject on the state of the prosthesis without conscious attention of the subject. Finally the optimalized EMG algorithm will be combined with the best functioning feedback modality to form a controlled TFP.

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Secondary

Measure	Time frame
nvt.	—

Countries

Netherlands

Outcome results

None listed

Source: NL-OMON (via WHO ICTRP)