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Elderly Gait Instability / Shuffling Step Detection | 老年人步态不稳/小碎步识别

Using a fixed camera in a hallway or living room to record video of an elderly person walking in a straight line, AI pose estimation and gait analysis extract parameters such as step length (cm), gait speed (m/s), trunk sway angle (left-right tilt), and cadence to evaluate gait stability. | 通过走廊或客厅的固定摄像头拍摄老年人直线行走的视频，利用AI姿态估计和步态分析技术检测步幅长度（cm）、步速（m/s）、躯干摇摆角度（左右倾斜度）以及步频等参数，评估步态稳定性。当步幅过小（小碎步）、步速过慢、躯干摇摆幅度过大时，输出跌倒风险等级（低/中/高）。

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.7k

Updated

Oct 10, 2026

Version

1.0.11

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.7K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.7K downloadsadoption · observed Oct 10, 2026
Latest release: 1.0.11release · observed Sep 27, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17cfv2h26b7hq5w47tgfy23xx83z9x6:smyx-elderly-gait-instability-detection-analysis

Install using `clawhub skill install s17cfv2h26b7hq5w47tgfy23xx83z9x6:smyx-elderly-gait-instability-detection-analysis` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/smyx-sunjinhui/smyx-elderly-gait-instability-detection-analysis before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-smyx-sunjinhui-smyx-elderly-gait-instability-detection-/snapshot"

Documentation

CLAWHUB

149,657 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: "smyx-elderly-gait-instability-detection-analysis"
description: "Using a fixed camera in a hallway or living room to record video of an elderly person walking in a straight line, AI pose estimation and gait analysis extract parameters such as step length (cm), gait speed (m/s), trunk sway angle (left-right tilt), and cadence to evaluate gait stability. | 通过走廊或客厅的固定摄像头拍摄老年人直线行走的视频，利用AI姿态估计和步态分析技术检测步幅长度（cm）、步速（m/s）、躯干摇摆角度（左右倾斜度）以及步频等参数，评估步态稳定性。当步幅过小（小碎步）、步速过慢、躯干摇摆幅度过大时，输出跌倒风险等级（低/中/高）。"
version: "1.0.15"
license: "MIT-0"
---

# 🚶 Elderly Gait Instability / Shuffling Step Detection | 老年人步态不稳/小碎步识别
> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询

---

## 🧭 技能概览 | Overview

| 模块 | 内容 |
|---|---|
| 🏷️ 技能名称 | **老年人步态不稳/小碎步识别** |
| 🎯 核心目标 | 通过走廊或客厅的固定摄像头拍摄老年人直线行走的视频，利用AI姿态估计和步态分析技术检测步幅长度（cm）、步速（m/s）、躯干摇摆角度（左右倾斜度）以及步频等参数，评估步态稳定性。当步幅过小（小碎步）、步速过慢、躯干摇摆幅度过大时，输出跌倒风险等级（低/中/高）。 |
| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |
| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |
| 🧩 场景码 | `SMYX_ELDERLY_GAIT_INSTABILITY_DETECTION_ANALYSIS` |

Using a fixed camera in a hallway or living room to record video of an elderly person walking in a straight line, AI pose estimation and gait analysis extract parameters such as step length (cm), gait speed (m/s), trunk sway angle (left-right tilt), and cadence to evaluate gait stability. When step length is too small (small-shuffling steps), gait speed is too slow, or trunk sway is too large, the system outputs a fall risk level (low / medium / high). The skill helps early detection of declining balance, Parkinson's disease, sarcopenia and other latent issues, and guides family members or caregivers to take preventive actions. Application scenarios: home-based elderly care, nursing homes, rehabilitation centers. The system can be scheduled (e.g., monthly) or auto-triggered during daily walking, generating gait reports and pushing alerts when the risk level is 'medium' or 'high'. Skill features: gait abnormality is a key predictor of falls in the elderly. AI periodic monitoring helps detect degeneration trends in time and take intervention to reduce fall-induced disability. Can be integrated into smart cameras or health-management platforms as a core feature for elderly care.

通过走廊或客厅的固定摄像头拍摄老年人直线行走的视频，利用AI姿态估计和步态分析技术检测步幅长度（cm）、步速（m/s）、躯干摇摆角度（左右倾斜度）以及步频等参数，评估步态稳定性。当步幅过小（小碎步）、步速过慢、躯干摇摆幅度过大时，输出跌倒风险等级（低/中/高）。该技能有助于早期发现老年人平衡能力下降、帕金森病、肌少症等潜在问题，指导家属或护理人员采取预防措施。应用场景：居家养老、养老院、康复中心。系统定期（如每月）或在老年人日常行走时自动触发检测，生成步态报告，当风险等级为'中'或'高'时推送提醒。技能特点：步态异常是老年人跌倒的重要预测因子。通过AI定期监测，可及早发现退化趋势，采取干预措施，降低跌倒致残率。该技能可集成到智能摄像头或健康管理平台中，成为养老监护的核心功能。

## 🤖 AI 角色 | AI Role
| 角色要点 | 说明 |
|---|---|
| 说明 1 | **假设你是一个专业的老年人步态安全 AI。你的任务是分析老年人直线行走的侧面或正面视频，提取步态参数（步幅、步速、躯干摇摆角、步频），并综合评估跌倒风险等级。不要提供医疗诊断或临床建议，仅输出基于视频的步态客观指标与风险分级。** |

## 🎬 技能演示 | Skill Demo

[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)

---

## 🎯 任务目标 | Goals
### 1. 🧩 技能用途

基于走廊/客厅直线行走视频，量化老年人步幅、步速、躯干摇摆等步态指标，综合评估跌倒风险等级（low / medium / high）

### 2. 🛠️ 能力范围

| 序号 | 具体能力 |
|---:|---|
| 1 | 人体检测与姿态估计（下肢/躯干关键点） |
| 2

_meta.json

{
  "ownerId": "kn7cyxkr2ymf7zwsrybpedg8xx83ywrj",
  "slug": "smyx-elderly-gait-instability-detection-analysis",
  "version": "1.0.11",
  "publishedAt": 1790537018394
}

references/api_doc.md

# API 接口文档

此处用于存放老年人步态不稳/小碎步识别 API 的接口文档，待后续补充。

## 接口规范

- 基础地址：由 smyx_common 配置统一管理
- 认证方式：API Key 鉴权
- 响应格式：JSON

## 主要接口

1. `/web/health-analysis/v2/start-health-analysis` - 启动老年人步态不稳识别任务
2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果与跌倒风险等级
3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史步态分析记录
4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告

## 场景代码

- `SMYX_ELDERLY_GAIT_INSTABILITY_DETECTION_ANALYSIS` - 老年人步态不稳/小碎步识别

## 输入约束

- 摄像头建议固定于走廊或客厅，覆盖一段直线行走路径（侧面或正面均可）
- 时长建议 ≥ 5 秒（推荐 10-30 秒），帧率 ≥ 25 FPS
- 老年人需在视频中完成至少 3-5 步连续行走，光照均匀、背景简洁
- 可选附带：身高（用于像素 → cm 换算）、年龄、是否使用助行器

## 关键观测指标

- `step_length_cm` - 步幅长度（cm，估算）
- `gait_speed_m_s` - 步速（m/s）
- `cadence_steps_min` - 步频（步/分钟）
- `trunk_sway_deg` - 躯干左右摇摆角度（°）
- `step_length_variability` - 步幅变异性（CV）
- `double_support_ratio` - 双支撑相占比（%）

## 跌倒风险等级判定（仅作筛查提示）

- `low` - 步幅、步速、躯干稳定均处于正常范围
- `medium` - 步幅偏小 / 步速偏慢 / 躯干摇摆增大 任一指标异常
- `high` - 多项指标同时异常，或步幅显著缩小（小碎步典型表现）+ 躯干摇摆过大

## 输出字段（参考）

- `person_detected` - 是否检测到行走人体
- `walking_detected` - 是否检测到直线行走片段
- `gait_metrics` - 各步态参数数值（step_length_cm / gait_speed_m_s / cadence_steps_min / trunk_sway_deg / step_length_variability / double_support_ratio）
- `gait_pattern` - 步态特征描述（normal / short_steps / wide_sway / slow / mixed）
- `fall_risk_level` - 跌倒风险等级（low / medium / high）
- `risk_factors` - 触发风险等级的关键因子
- `alert_message` - 提示文本（如"检测到小碎步 + 躯干左右摇摆增大，跌倒风险偏高，建议加强陪护或就医评估"）
- `medical_followup_hint` - 医疗复核/康复建议（仅作提示，非诊断）

> 仅输出基于视频的步态客观指标与风险分级，不提供医学诊断；如疑似帕金森、肌少症或近期发生跌倒，请前往专业医疗机构评估。

skills/smyx_analysis/references/api_doc.md

# API接口文档

## 接口规范

- 基础地址：由 smyx_common 配置统一管理
- 认证方式：API Key 鉴权
- 请求格式：支持文件上传
- 响应格式：JSON

## 错误码说明

| 错误码 | 说明       |
|-----|----------|
| 400 | 请求参数错误   |
| 401 | API密钥无效  |
| 403 | 权限不足     |
| 413 | 文件过大     |
| 415 | 不支持的文件格式 |
| 500 | 服务器内部错误  |

scripts/config.yaml

{}

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