Repawse 宠物康复外骨骼 by Leijing Zhou is a highly esteemed winner of the very prestigious 2025 A' Design Award 银奖 in 宠物护理、玩具、用品与动物产品设计 Competition Category.

银宠物用品· 2025

Repawse 宠物康复外骨骼

by Leijing Zhou

Client: Zhejiang University

A' Design Award 银奖 Winner in 宠物用品 Category

75,206

Verified Award Winner

Verify Award Status for #172611

View at A' Design Award Press Release Award Badge

Colors

The Design

About Repawse 宠物康复外骨骼

Repawse是一款专为后肢功能障碍犬只设计的康复外骨骼。表面肌电传感器采集健康前肢的肌肉信号，微控制器据此预测运动意图，随后由直线致动器实时驱动后肢支撑结构运动，使行走保持协调而自然。机架采用铝合金材质，内衬为柔软记忆海绵，鞋底则使用防滑橡胶。各部件依据身体扫描数据进行3D打印，实现个性化贴合，带来更佳的舒适体验。

The Recognition

About the A' Design Award 银奖

Repawse 宠物康复外骨骼是 A' Design Award 银奖得主，这是授予顶级、华美而令人印象深刻的设计的极为崇高的认可。银奖得主是极其卓越、极具创造力的作品，展现出其设计师杰出的专业技能、才华与敏锐。预计Repawse 宠物康复外骨骼将成为一件出色的典范之作，兼具非凡的专业性与深刻的创新性。这件赢得 A' Design Award 银奖的设计是一项备受瞩目、令人钦佩的发明，造福并拓展艺术、科学、设计和技术的边界。Repawse 宠物康复外骨骼是一件令人羡慕的创作，它唤起渴望，带来积极的情感，并激发惊叹与赞叹。

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: In response to the rehabilitation needs of disabled pets, we have developed a canine rehabilitation exoskeleton based on surface electromyographic (sEMG) control. By collecting sEMG signals from the healthy forelimb, the system drives the hindlimb actuators in real time to synchronise gait. Combined with 3D printing for custom design, it provides precise movement assistance for disabled dogs, embodying the technological protection of animal life dignity.
Dimensions & Packaging: Dimensions: 220mm × 200mm × 540mm
Materials: Aluminum alloy frame, soft memory foam lining, rubber soles
Technology: Surface EMG sensors, linear actuators, microcontroller-based control
Power source: Rechargeable lithium battery, 7.4V, 5000mAh
Tags: Pet Rehabilitation, Animal Welfare, Exoskeleton, sEMG Signal, Active Control, 3D-Printing, Customized Design, Assistive Mobility
Production Technology: The exoskeleton is produced through advanced 3D printing technology allowing individual customization based on precise body scans. Lightweight, durable materials, including soft memory foam lining, aluminum alloy for structural parts, and anti-slip rubber soles, ensure strength, comfort, and safety in daily use.
Design Challenge: The primary challenge was accurately interpreting animal intention through muscle signals, with few existing precedents or standards. Historically, disabled pets faced limited and uncomfortable assistive solutions. Technologically, creating lightweight yet robust actuators and ensuring comfort required extensive material research, innovative mechanical design, and iterative prototyping with real pets.
Research: This project originated from a news report on prosthetic limbs for disabled pets, highlighting the pros and cons of current solutions. Inspired, we explored transferring active-control exoskeleton technology—originally developed for stroke patients—to veterinary rehabilitation. Through extensive field research, EMG data collection from animals, iterative predictive modeling, and mechanical prototyping, we successfully created an intelligent, active-assist exoskeleton for pets.
Inspiration: The inspiration for this project originated from a news report highlighting customized prosthetics for disabled pets, exposing significant limitations in current solutions. Coupled with my personal experience of caring for my own dog after its hindlimb injury, I recognized the broader societal need to extend humane, intelligent rehabilitation technology from human healthcare into pet care, ultimately enhancing animal welfare.
Project Duration: The project started in 2023 in Hangzhou and finished in March 2025 in Hangzhou.
Operation Flow: When the dog walks, sensors detect muscle signals (sEMG) from the healthy forelimb. These signals are processed to predict the movement intention of the impaired hindlimb, triggering linear actuators in real time. This active, intuitive assistance ensures natural movement, aiding rehabilitation efficiently.
Team Members: Menghan Li
Leijing Zhou
Xinmiao Shen
Xiaofei Gong
Xiaotong Guan
Ding Ding
Jinjie Li
Qianyi Wang
Keyin Chen
Zixiang Wang
Zihan Zhang