Algorithms to Detect In-Home Falls of Elderly Using Structured Light Sensing
Algorithms to Detect In-Home Falls of Elderly Using Structured Light Sensing
批准号:
9902762
负责人:
PAUL GIBSON
金额:
$29.98万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-02-15 至 2023-01-31
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
中文摘要
摘要
每年65岁及以上的人中,超过1/4的人摔倒。在跌倒的人中,每五人中就有一人患有严重的
受伤,如骨折或头部受伤。每年有超过80万名患者因跌倒而住院
受伤,通常是因为头部受伤或髋部骨折。研究发现,身体健康的风险增加。
以及与摔倒后长时间躺在地板上有关的生理并发症,原因是
起不来。独居的老年人在跌倒后有很大的延迟援助的风险。一个低点-
能够自动检测老年人家中跌倒的成本低、不显眼的系统可能会有所帮助
大大减少跌倒后延误援助的发生率。该项目将开发一种创新的新
居家坠落监测系统,解决了与其他系统的许多实际问题。技术上的
方法使用结构光。结构光传感创建场景的3D点云以进行检测
运动序列,这将允许自动检测人的跌倒。这有很多好处
这种方法;老年人不需要携带电子设备或摔倒后采取行动,视频
不使用会对老年人造成隐私问题的图像,系统可以在
与基于摄像头的方法不同,该系统不太容易受到错误警报的影响,而不是振动或
声学坠落监测可以推断坠落。结构光传感跌倒检测产品旨在成为一种
当今使用的家庭警报系统的可选附件。它将与多个家庭警报供应商合作
系统。它将与可穿戴按钮并行操作,发出警报信号。一旦结构光传感下降
检测到摔倒,就会激活警报系统,就像按下可穿戴式按钮一样。相同
协议将会得到遵守。在这些系统中,操作员首先会尝试与说话人交谈
供应商的居家警报系统的电话。如果他们不能与人交流,他们就会开始工作
通过当地人的来电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认为简单的可穿戴按钮不够用,则会使用
被监视人员的解决方案。
英文摘要
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.
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