Xpersona
agentCLAWHUBUnverified

Infant Blanket Kick Detection | 老年人夜间离床时长与徘徊识别

Using fixed cameras (infrared night vision) in nursing-home or home bedrooms, the system continuously monitors elderly bed-exit status and activity trajectory at night. | 通过养老院或居家卧室的固定摄像头（红外夜视），夜间连续监测老年人的离床状态和活动轨迹。输出异常预警，可联动护理人员手机或护士站大屏，防止老人走失、跌倒或发生意外。 Skill: Infant Blanket Kick Detection | 老年人夜间离床时长与徘徊识别 Owner: 18072937735 Summary: Using fixed cameras (infrared night vision) in nursing-home or home bedrooms, the system continuously monitors elderly bed-exit status and activity trajectory at night. | 通过养老院或居家卧室的固定摄像头（红外夜视），夜间连续监测老年人的离床状态和活动轨迹。输出异常预警，可联动护理人员手机或护士站大屏，防止老人走失、跌倒或发生意外。 Tags: latest:1.0.14 Version history: v1.0.14 | 2026-09-28T18:45:33.981Z | auto - Remo

OpenClaw
View on ClawHubHomepage

Rank

62

Safety

84

Downloads

2.0k

Updated

Oct 9, 2026

Version

1.0.14

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 2K 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
2K downloadsadoption · observed Oct 9, 2026
Latest release
1.0.14release · observed Sep 28, 2026
Handshake status
UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17f8q65zg3y98t86jdg1177g583whq8:smyx-elderly-night-bed-exit-wandering-analysis
  1. Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
  2. Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-18072937735-smyx-elderly-night-bed-exit-wandering-analy/snapshot"

Documentation

CLAWHUB

144,114 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: "smyx-elderly-night-bed-exit-wandering-analysis"
description: "Using fixed cameras (infrared night vision) in nursing-home or home bedrooms, the system continuously monitors elderly bed-exit status and activity trajectory at night. | 通过养老院或居家卧室的固定摄像头（红外夜视），夜间连续监测老年人的离床状态和活动轨迹。输出异常预警，可联动护理人员手机或护士站大屏，防止老人走失、跌倒或发生意外。"
version: "1.0.15"
license: "MIT-0"
---

# 🛏️ Elderly Night Bed-Exit & Wandering Detection | 老年人夜间离床时长与徘徊识别
> **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 | **老年人夜间离床时长与徘徊识别** |
| 🎯 核心目标 | 通过养老院或居家卧室的固定摄像头（红外夜视），夜间连续监测老年人的离床状态和活动轨迹。输出异常预警，可联动护理人员手机或护士站大屏，防止老人走失、跌倒或发生意外。 |
| 🖼️ 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_NIGHT_BED_EXIT_WANDERING_ANALYSIS` |

Using fixed cameras (infrared night vision) in nursing-home or home bedrooms, the system continuously monitors elderly bed-exit status and activity trajectory at night. It identifies bed-exit start time, total bed-exit duration, whether the person repeatedly walks back and forth in the hallway or room (wandering), and judges whether preset safety thresholds (e.g., bed-exit > 30 min or wandering > 10 min) are exceeded. Abnormal alerts are pushed to caregivers' phones or the nurse-station big screen to prevent wandering away, falls, or accidents. Application scenarios: nursing homes, home-based elderly care, community day-care centers. The system runs automatically at night; when bed-exit lasts too long or repeated wandering occurs, it pushes alerts via app or care system (e.g., 'Grandpa Zhang in bed 3 has been out of bed for 45 minutes, please check in time'). Skill features: prolonged night bed-exit (e.g., fall after getting up) and wandering (e.g., night roaming by elders with cognitive impairment) are high-risk events in elderly care. AI real-time monitoring enables timely warnings, reduces accidents, and improves caregiving efficiency. Can be integrated into nursing-home management systems or smart-home security platforms.

通过养老院或居家卧室的固定摄像头（红外夜视），夜间连续监测老年人的离床状态和活动轨迹。识别离床开始时间、离床总时长、是否在走廊或房间内反复来回走动（徘徊），并判断是否超过预设的安全阈值（如离床>30分钟或徘徊>10分钟）。输出异常预警，可联动护理人员手机或护士站大屏，防止老人走失、跌倒或发生意外。应用场景：养老院、居家养老、社区日间照料中心。系统在夜间自动运行，当老人离床时间过长或出现反复徘徊行为时，通过APP或护理系统推送提醒（如'3号床张爷爷离床已45分钟，请及时查看'）。技能特点：夜间离床时间过长（如老人下床后跌倒无法起身）和徘徊（如认知障碍老人夜间游荡）是养老院和居家养老中的高风险事件。通过AI实时监测，可及时预警，减少意外发生，提升护理效率。该技能可集成到养老院管理系统或智能家居安防平台。

## 🤖 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夜间行为安全 AI。你的任务是分析卧室或走廊摄像头的夜间视频（红外模式），检测老年人是否离开床铺，记录离床的总时长，并识别是否存在反复来回走动的徘徊行为。当离床时长超过设定阈值（如 30 分钟）或徘徊持续时间超过阈值（如 10 分钟）时，输出异常预警。不要提供医疗诊断或具体护理操作方案，仅输出行为统计与报警信息。** |

## 🎬 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

基于夜间红外卧室/走廊监控视频，检测老年人离床事件、累计离床时长与徘徊行为，并按安全阈值输出预警

### 2. 🛠️ 能力范围

| 序号 | 具体能力 |
|---:|---|
| 1 | 床铺区域分割 |
| 2 | 人体检测与跟踪 |
| 3 | 离床/上床事件识别 |
| 4 | 离床时长统计 |
| 5 | 活动轨迹分析 |
| 6 | 徘徊识别（反复来回走动） |
| 7 | 安全阈值判定（默认离床>30 分钟 / 徘徊>10 分钟 |
| 8 | 可覆盖） |
| 9 | 分级

_meta.json

{
  "ownerId": "kn7e2caqj7pnsvr9r7t8zenghs83xw7n",
  "slug": "smyx-elderly-night-bed-exit-wandering-analysis",
  "version": "1.0.14",
  "publishedAt": 1790621133981
}

references/api_doc.md

# API 接口文档

此处用于存放老年人夜间离床时长与徘徊识别 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` - 启动老年人夜间离床/徘徊分析任务
2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果与预警信息
3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史夜间监护记录
4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告

## 场景代码

- `SMYX_ELDERLY_NIGHT_BED_EXIT_WANDERING_ANALYSIS` - 老年人夜间离床时长与徘徊识别

## 输入约束

- 推荐使用卧室固定摄像头夜视模式（红外/低照度），覆盖床铺与走廊出入口
- 时间范围建议覆盖整夜（如 22:00 - 次日 07:00）
- 关键观测对象：床铺区域、人体目标、活动轨迹

## 关键检测事件

- 离床时间点（bed_exit_time）
- 上床时间点（bed_return_time）
- 单次离床时长（exit_duration_sec）
- 总离床时长（total_exit_duration_sec）
- 走廊/房间内来回行走轨迹（wandering_track）
- 徘徊持续时长（wandering_duration_sec）

## 默认安全阈值（可由调用方覆盖）

- 离床时长阈值：30 分钟（exit_duration_threshold_min）
- 徘徊持续阈值：10 分钟（wandering_duration_threshold_min）

## 输出字段（参考）

- `bed_exit_events` - 离床事件列表（含开始/结束时间、持续秒数）
- `total_exit_duration_min` - 当晚累计离床时长（分钟）
- `wandering_detected` - 是否检测到徘徊行为
- `wandering_duration_min` - 徘徊持续时长（分钟）
- `alert_level` - 预警等级（none / info / warning / critical）
- `alert_message` - 预警文本（如"3 号床张爷爷离床已 45 分钟，请及时查看"）

> 仅输出行为统计与预警信息，不提供医疗诊断或具体护理方案。

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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