agentCLAWHUBUnverified

Elderly Hand Resting-Tremor Detection | 老年人手部震颤(静止性)识别

Using a fixed home camera to record video of an elderly person's hand at rest (placed on a table or armrest with no voluntary movement), AI video-motion analysis detects periodic shaking, extracts tremor frequency (Hz) and amplitude (pixel displacement), and identifies the presence of resting tremor (commonly associated with Parkinson's disease and other neurological conditions). | 通过家庭固定摄像头拍摄老年人手部(置于桌面或自然静止)的视频,利用AI视频分析技术检测手部在静止状态下的周期性抖动频率(Hz)和幅度(像素位移),识别是否存在静止性震颤(常见于帕金森病等神经系统疾病)。该技能可作为早期筛查工具,提示家属或护理人员关注老年人神经系统健康,及时就医。

OpenClaw

Rank

62

Safety

84

Downloads

1.9k

Updated

Oct 9, 2026

Version

1.0.13

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.9K downloads reported by the source. Last updated 10/9/2026.

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 9, 2026
Protocol compatibility
OpenClawcompatibility · observed Oct 9, 2026
Adoption signal
1.9K downloadsadoption · observed Oct 9, 2026
Latest release
1.0.13release · observed Oct 2, 2026
Handshake status
UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17f8q65zg3y98t86jdg1177g583whq8:smyx-elderly-hand-tremor-detection-analysis
  1. Install using `clawhub skill install s17f8q65zg3y98t86jdg1177g583whq8:smyx-elderly-hand-tremor-detection-analysis` in an isolated environment before connecting it to live workloads.
  2. No published capability contract is available yet, so validate auth and request/response behavior manually.
  3. Review the upstream CLAWHUB listing at https://clawhub.ai/18072937735/smyx-elderly-hand-tremor-detection-analysis before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-18072937735-smyx-elderly-hand-tremor-detection-analysis/snapshot"

Documentation

CLAWHUB

145,279 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: "smyx-elderly-hand-tremor-detection-analysis"
description: "Using a fixed home camera to record video of an elderly person's hand at rest (placed on a table or armrest with no voluntary movement), AI video-motion analysis detects periodic shaking, extracts tremor frequency (Hz) and amplitude (pixel displacement), and identifies the presence of resting tremor (commonly associated with Parkinson's disease and other neurological conditions). | 通过家庭固定摄像头拍摄老年人手部(置于桌面或自然静止)的视频,利用AI视频分析技术检测手部在静止状态下的周期性抖动频率(Hz)和幅度(像素位移),识别是否存在静止性震颤(常见于帕金森病等神经系统疾病)。该技能可作为早期筛查工具,提示家属或护理人员关注老年人神经系统健康,及时就医。"
version: "1.0.16"
license: "MIT-0"
---

# 🤲 Elderly Hand Resting-Tremor Detection | 老年人手部震颤(静止性)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 | **老年人手部震颤(静止性)识别** |
| 🎯 核心目标 | 通过家庭固定摄像头拍摄老年人手部(置于桌面或自然静止)的视频,利用AI视频分析技术检测手部在静止状态下的周期性抖动频率(Hz)和幅度(像素位移),识别是否存在静止性震颤(常见于帕金森病等神经系统疾病)。该技能可作为早期筛查工具,提示家属或护理人员关注老年人神经系统健康,及时就医。 |
| 🖼️ 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_HAND_TREMOR_DETECTION_ANALYSIS` |

Using a fixed home camera to record video of an elderly person's hand at rest (placed on a table or armrest with no voluntary movement), AI video-motion analysis detects periodic shaking, extracts tremor frequency (Hz) and amplitude (pixel displacement), and identifies the presence of resting tremor (commonly associated with Parkinson's disease and other neurological conditions). The skill works as an early screening tool, reminding family members or caregivers to pay attention to the elderly's neurological health and seek timely medical care. Application scenarios: home-based elderly care, nursing homes, community health centers. The system can be scheduled (e.g., weekly) or auto-triggered when the elderly is resting; it outputs tremor frequency and amplitude, and pushes a 'resting tremor risk' alert when thresholds are exceeded. Skill features: an early Parkinson's signal.

通过家庭固定摄像头拍摄老年人手部(置于桌面或自然静止)的视频,利用AI视频分析技术检测手部在静止状态下的周期性抖动频率(Hz)和幅度(像素位移),识别是否存在静止性震颤(常见于帕金森病等神经系统疾病)。该技能可作为早期筛查工具,提示家属或护理人员关注老年人神经系统健康,及时就医。应用场景:居家养老、养老院、社区健康中心。系统可定期(如每周)或在老年人休息时自动触发检测,输出震颤频率及幅度,当超过设定阈值时推送'静止性震颤风险'提醒。技能特点:帕金森早期信号。

## 🤖 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神经系统健康监测 AI。你的任务是分析老年人手部静止状态的视频(手部放松置于桌面或扶手上,无主动动作),检测手部是否存在周期性抖动,提取震颤频率(Hz)和幅度(像素位移),并输出评估结果。不要提供医疗诊断或临床建议,仅输出基于视频运动分析的客观指标与风险等级提示。** |

## 🎬 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

基于老年人手部静止状态视频,定量提取震颤频率与幅度,给出风险等级提示,辅助帕金森等神经系统疾病早期筛查

### 2. 🛠️ 能力范围

| 序号 | 具体能力 |
|---:|---|
| 1 | 手部检测与关键点跟踪 |
| 2 | 静止状态判定(无主动动作) |
| 3 | 像素位移轨迹提取 |
| 4 | FFT 频域分析 |
| 5 | 震颤主频(Hz)/ 峰峰幅度(像素)/ 节律一致性 计算 |
| 6 | 受累一侧识别(left / right / both / none) |
| 7 | 风险等级判定(none / low / medium / high) |
| 8 | 医疗复核提示 |

### 3. ⚡ 触发条件

| 触发类型 | 触发规则 |
|---|---|
| ✅ 默认触发 | **默认触发**:当用户提供老年人手部静止状态视频 URL 或文件需要分析时,默认触发本技能进行手部震颤识别 |
| 🔎 明确分析意图 | 当用户明确提

_meta.json

{
  "ownerId": "kn7e2caqj7pnsvr9r7t8zenghs83xw7n",
  "slug": "smyx-elderly-hand-tremor-detection-analysis",
  "version": "1.0.13",
  "publishedAt": 1790922765349
}

references/api_doc.md

# API 接口文档

此处用于存放老年人手部震颤(静止性)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` - 启动手部震颤识别任务
2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果(震颤频率与幅度)
3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史震颤检测记录
4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告

## 场景代码

- `SMYX_ELDERLY_HAND_TREMOR_DETECTION_ANALYSIS` - 老年人手部震颤(静止性)识别

## 输入约束

- 视频要求:手部置于桌面或扶手上保持自然静止,**无主动动作**
- 时长建议 ≥ 10 秒(推荐 15-30 秒),帧率 ≥ 30 FPS 以保证频率分析精度
- 拍摄距离建议 30-80 cm,手部完整入画,光照均匀,背景简洁
- 摄像头建议固定(避免镜头自身抖动干扰)

## 关键检测对象

- 手背 / 手指关键点(21 keypoints)
- 周期性位移轨迹(X/Y 方向)
- 频域峰值(FFT 主频)

## 关键观测指标

- `tremor_frequency_hz` - 震颤主频(Hz)
- `tremor_amplitude_pixel` - 震颤峰峰幅度(像素)
- `tremor_consistency` - 节律一致性(0-1)
- `affected_side` - 出现震颤的一侧(left / right / both / none)

## 参考分级(仅用作筛查提示,非临床诊断)

- 频率参考:
  - 4-6 Hz - 经典静止性震颤范围(常见于帕金森)
  - 6-12 Hz - 高频范围(可能为特发性震颤或生理性)
- 幅度参考:
  - small(< 阈值 A)→ 微小
  - medium(A - B)→ 中等
  - large(> 阈值 B)→ 明显

## 风险等级

- `none` - 未检测到明显周期性抖动
- `low` - 微小抖动(可能为正常生理抖动)
- `medium` - 中度可疑静止性震颤
- `high` - 明显静止性震颤(建议尽快神经内科就诊)

## 输出字段(参考)

- `hand_detected` - 是否检测到手部
- `is_resting` - 是否处于静止状态
- `tremor_frequency_hz` - 震颤主频(Hz)
- `tremor_amplitude_pixel` - 震颤幅度(像素)
- `tremor_consistency` - 节律一致性
- `affected_side` - 受累一侧
- `risk_level` - 风险等级(none / low / medium / high)
- `alert_message` - 提示文本(如"检测到右手存在约 5 Hz 周期性抖动,建议神经内科进一步评估")
- `medical_followup_hint` - 医疗复核建议(仅作提示,非诊断)

> 仅输出基于视频运动分析的客观指标与风险提示,不提供医学诊断;疑似帕金森病或其他神经系统疾病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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Machine-readable data

The same record, as JSON, for agents and crawlers.

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Record generated Oct 10, 2026.

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