Algorithms to Detect In-Home Falls of Elderly Using Structured Light Sensing
使用结构光传感检测老人家中跌倒的算法
基本信息
- 批准号:9902762
- 负责人:
- 金额:$ 29.98万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-02-15 至 2023-01-31
- 项目状态:已结题
- 来源:
- 关键词:3-DimensionalAcousticsAdultAgingAlgorithmsCaregiversCessation of lifeCommunication MethodsConsultCraniocerebral TraumaDarknessDataData SetDetectionDevelopmentDevicesElderlyElectronicsEngineeringEvaluationFall preventionFloorFurnitureHealth PromotionHip FracturesHip InjuriesHome environmentHospital CostsHumanImageIncidenceInjuryLightMedicalMedical Care CostsMinnesotaMonitorMotionPatientsPersonsPhasePhysiologicalPopulationPrincipal InvestigatorPrivacyProtocols documentationResearchRiskScienceSignal TransductionStructureSystemTechnologyTelephoneUniversitiesVendorVisible RadiationVisitWireless TechnologyWorkbasebonecomputerized data processingcostexperiencefall injuryfall riskfallshuman old age (65+)innovationmid-career facultyphase 1 testingsensorsevere injurysuccessvibration
项目摘要
Abstract
Each year more than one out of four people 65 and older falls. Of those that fall one out of five has a serious
injury such as broken bones or a head injury. Over 800,000 patients a year are hospitalized because of a fall
injury, most often because of a head injury or hip fracture. Studies have found an increased risk of physical
and physiological complications associated with prolonged periods of lying on the floor following a fall, due to
an inability to get up. Older adults living alone are at great risk of delayed assistance following a fall. A low-
cost, unobtrusive system capable of automatically detecting falls in the homes of older adults could help
significantly reduce the incidence of delayed assistance after a fall. This project will develop an innovative new
in-home fall monitoring system that solves many practical problems with other systems. The technical
approach uses structured light. Structured light sensing creates 3D point clouds of a scene to allow detection
of motion sequences which will allow for the automatic detection of a person’s fall. There are many benefits of
this approach; the elderly person is not required to carry an electronic device or take action after the fall, video
images that would create a privacy concern for the elderly person are not used, the system can work in
darkness unlike camera based approaches, and the system is less susceptible to false alarms than vibration or
acoustic fall monitoring that infer a fall. The structured light sensing fall detection product is intended to be an
optional accessory to in-home alert systems in use today. It will work with multiple vendors of in-home alert
systems. It will operate in parallel with wearable buttons to signal an alert. Once the structured light sensing fall
detection identifies a fall it will activate the alert system the same way as a wearable button press. The same
protocol would be followed. In these systems an operator would first try to talk to the person with the speaker
phone of the vendors’ in-home alert system. If they cannot communicate with the person, they start working
through a call list of local people to check on the home. The structured light sensing fall detection system
would be used if caregivers decide for various reasons that a simple wearable button is not an adequate
solution for the person being monitored.
摘要
每年超过四分之一的65岁及以上的福尔斯会摔倒。五分之一的人有严重的
受伤,如骨折或头部受伤。每年有80多万病人因跌倒住院
受伤,通常是因为头部受伤或髋部骨折。研究发现,
以及与跌倒后长时间躺在地板上相关的生理并发症,
无法起身独居的老年人在跌倒后延迟援助的风险很大。一个低-
一种能够自动检测老年人家中福尔斯跌倒的廉价、不显眼的系统可能会有所帮助
显著降低跌倒后延迟援助的发生率。该项目将开发一种创新的
家庭跌倒监测系统,解决了许多与其他系统的实际问题。技术
方法使用结构光。结构光传感创建场景的3D点云,以允许检测
这将允许自动检测一个人的跌倒。有很多好处
这种方法;老年人不需要携带电子设备或采取行动后,下降,视频
不使用会对老年人造成隐私问题的图像,系统可以在
黑暗不像基于相机的方法,并且系统比振动或
声音跌倒监测可以推断跌倒。结构光感测跌倒检测产品旨在成为
目前使用的家用警报系统的可选附件。它将与多个供应商的家庭警报
系统.它将与可穿戴按钮并行操作,以发出警报信号。一旦结构光感测下降,
检测识别跌倒,其将以与可穿戴按钮按压相同的方式激活警报系统。相同的
将遵循协议。在这些系统中,操作员将首先尝试与说话者交谈
供应商的家庭警报系统的电话。如果他们不能与人沟通,他们开始工作,
通过当地人的电话名单来查看家里的情况结构光传感跌倒检测系统
如果护理人员出于各种原因决定简单的可穿戴按钮不足以
为被监视的人提供解决方案。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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PAUL GIBSON其他文献
PAUL GIBSON的其他文献
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$ 29.98万 - 项目类别:
Using Structured Light Sensing with Machine Learning to Detect Unwitnessed In-Home Falls
使用结构光传感和机器学习来检测无人目击的家庭跌倒
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