所属方向: 传感、识别与安全

步态跌倒与移动监测

统计基于当前已索引 question 数据，来源缺失不影响问题展示。

问题/痛点

来源

2024

全部问题

36 条

全部研究问题现实痛点

help研究问题步态跌倒与移动监测

如何在短序列步态数据中，通过耳戴式IMU实现高精度的步态周期分割？

UbiComp '24GCCRR: A Short Sequence Gait Cycle Segmentation Method Based on Ear-Worn IMU

help研究问题步态跌倒与移动监测

如何利用步态特征曲线（Gait Characteristic Curve）提升步态周期分割的准确性与鲁棒性？

UbiComp '24GCCRR: A Short Sequence Gait Cycle Segmentation Method Based on Ear-Worn IMU

help研究问题步态跌倒与移动监测

相较于腿部IMU，耳戴式IMU在家庭环境中的步态监测有哪些优势与挑战？

UbiComp '24GCCRR: A Short Sequence Gait Cycle Segmentation Method Based on Ear-Worn IMU

lightbulb现实痛点步态跌倒与移动监测

患者在家中难以采集长时直线步态数据，难以进行准确的步态周期分割。

UbiComp '24GCCRR: A Short Sequence Gait Cycle Segmentation Method Based on Ear-Worn IMU

help研究问题步态跌倒与移动监测

如何设计一个无校准且易于穿戴的系统，用于监测膝关节炎患者行走时的关节负担和肌肉力量？

UbiComp '24KneeGuard: A Calibration-free Wearable Monitoring System for Knee Osteoarthritis Gait Re-training via Effortless Wearing

help研究问题步态跌倒与移动监测

IMU（惯性测量单元）和sEMG（表面肌电传感器）如何通过融合特性实现膝关节生物力学信号的准确估算？

UbiComp '24KneeGuard: A Calibration-free Wearable Monitoring System for Knee Osteoarthritis Gait Re-training via Effortless Wearing

help研究问题步态跌倒与移动监测

跨模态注意力机制是否能够有效提升膝关节负载和肌肉力量估算的准确性？

UbiComp '24KneeGuard: A Calibration-free Wearable Monitoring System for Knee Osteoarthritis Gait Re-training via Effortless Wearing

lightbulb现实痛点步态跌倒与移动监测

膝关节炎患者难以便捷地监测步态中的关节负担和肌肉力量。

UbiComp '24KneeGuard: A Calibration-free Wearable Monitoring System for Knee Osteoarthritis Gait Re-training via Effortless Wearing

help研究问题步态跌倒与移动监测

现有基于惯性测量单元（IMU）的步数统计方法在特殊场景中会出现哪些问题？

UbiComp '24Earable and Wrist-worn Setup for Accurate Step Counting Utilizing Body-Area Electrostatic Sensing

help研究问题步态跌倒与移动监测

基于身体区域静电感应的步数统计方案能否提高准确性？

UbiComp '24Earable and Wrist-worn Setup for Accurate Step Counting Utilizing Body-Area Electrostatic Sensing

help研究问题步态跌倒与移动监测

身体区域静电感应方法在不同身体部位的部署中是否具有一致性和适应性？

UbiComp '24Earable and Wrist-worn Setup for Accurate Step Counting Utilizing Body-Area Electrostatic Sensing

lightbulb现实痛点步态跌倒与移动监测

现有手环在推购物车或随机手臂动作时无法准确数步。

UbiComp '24Earable and Wrist-worn Setup for Accurate Step Counting Utilizing Body-Area Electrostatic Sensing

help研究问题步态跌倒与移动监测

毫米波雷达如何在复杂室内环境中有效识别用户的步态？

UbiComp '24RDGait: A mmWave Based Gait Recognition System for Complex Indoor Environments Using Single-chip Radar

help研究问题步态跌倒与移动监测

仅通过速度估计，如何检测和消除雷达数据中的“鬼影”？

UbiComp '24RDGait: A mmWave Based Gait Recognition System for Complex Indoor Environments Using Single-chip Radar

help研究问题步态跌倒与移动监测

步态识别系统能否通过少量训练数据快速适应新的环境？

UbiComp '24RDGait: A mmWave Based Gait Recognition System for Complex Indoor Environments Using Single-chip Radar

lightbulb现实痛点步态跌倒与移动监测

室内步态识别系统部署复杂，精度受环境影响大。

UbiComp '24RDGait: A mmWave Based Gait Recognition System for Complex Indoor Environments Using Single-chip Radar

help研究问题步态跌倒与移动监测

如何利用智能手机中的惯性传感器采集的步态数据评估多种脑部疾病的风险？

UbiComp '23NeuralGait: Assessing Brain Health Using Your Smartphone

help研究问题步态跌倒与移动监测

不同步态阶段的关系是否能作为脑部疾病的病理学线索？

UbiComp '23NeuralGait: Assessing Brain Health Using Your Smartphone

help研究问题步态跌倒与移动监测

能否通过基于自注意力机制的模型改进多标签脑疾病风险评估的准确性？

UbiComp '23NeuralGait: Assessing Brain Health Using Your Smartphone

lightbulb现实痛点步态跌倒与移动监测

用户难以用便捷低成本的方法评估自身脑健康风险。

UbiComp '23NeuralGait: Assessing Brain Health Using Your Smartphone

help研究问题步态跌倒与移动监测

如何区分普通跌倒与生命危险的跌倒情景？

UbiComp '23LT-Fall: The Design and Implementation of a Life-threatening Fall Detection and Alarming System

help研究问题步态跌倒与移动监测

毫米波雷达如何准确检测跌倒后静止的躯体？

UbiComp '23LT-Fall: The Design and Implementation of a Life-threatening Fall Detection and Alarming System

help研究问题步态跌倒与移动监测

如何提高微运动（如呼吸与心跳）检测的精度以识别生命危险的跌倒？

UbiComp '23LT-Fall: The Design and Implementation of a Life-threatening Fall Detection and Alarming System

lightbulb现实痛点步态跌倒与移动监测

老人在跌倒后若不能及时获救可能面临生命危险。

UbiComp '23LT-Fall: The Design and Implementation of a Life-threatening Fall Detection and Alarming System

help研究问题步态跌倒与移动监测

如何结合运动传感器和定位信息更准确地识别人体活动模式？

UbiComp '23Ensemble Learning using Motion Sensors and Location for Human Activity Recognition

help研究问题步态跌倒与移动监测

长短期记忆网络（LSTM）和XGBoost的联合学习在人体活动分类中表现如何？

UbiComp '23Ensemble Learning using Motion Sensors and Location for Human Activity Recognition

help研究问题步态跌倒与移动监测

优化的特征和后处理步骤对运动状态识别的准确性有什么影响？

UbiComp '23Ensemble Learning using Motion Sensors and Location for Human Activity Recognition

lightbulb现实痛点步态跌倒与移动监测

用户在室内或交通方式难区分时，活动识别不准确。

UbiComp '23Ensemble Learning using Motion Sensors and Location for Human Activity Recognition

help研究问题步态跌倒与移动监测

如何结合mmWave雷达和低成本RGB-D相机实现跨模态步态再识别，特别是在人多、隐私敏感的场景中？

UbiComp '22Cross Vision-RF Gait Re-identification with Low-cost RGB-D Cameras and mmWave Radars

help研究问题步态跌倒与移动监测

如何利用深度度量学习来应对雷达和相机数据的时间不同步，从而提高多目标跨模态识别效率？

UbiComp '22Cross Vision-RF Gait Re-identification with Low-cost RGB-D Cameras and mmWave Radars

help研究问题步态跌倒与移动监测

是否可以利用mmWave雷达的镜面反射特性来提取步态特征并关联跨模态数据？

UbiComp '22Cross Vision-RF Gait Re-identification with Low-cost RGB-D Cameras and mmWave Radars

lightbulb现实痛点步态跌倒与移动监测

公共区域与隐私场景间的人体身份追踪缺乏高效、安全的跨模态技术。

UbiComp '22Cross Vision-RF Gait Re-identification with Low-cost RGB-D Cameras and mmWave Radars

help研究问题步态跌倒与移动监测

可视化可穿戴传感器数据如何支持临床医生远程评估多发性硬化患者的步态？

CHI '22'Are They Doing Better In The Clinic Or At Home': Understanding Clinicians? Needs When Visualizing Wearable Sensor Data Used In Remote Gait Assessments For People With Multiple Sclerosis

help研究问题步态跌倒与移动监测

哪些可视化设计元素（如热图和蜘蛛图）可以最有效地支持步态数据的解读与应用？

CHI '22'Are They Doing Better In The Clinic Or At Home': Understanding Clinicians? Needs When Visualizing Wearable Sensor Data Used In Remote Gait Assessments For People With Multiple Sclerosis

help研究问题步态跌倒与移动监测

整合患者背景信息与步态数据对临床医生的决策有何影响？

CHI '22'Are They Doing Better In The Clinic Or At Home': Understanding Clinicians? Needs When Visualizing Wearable Sensor Data Used In Remote Gait Assessments For People With Multiple Sclerosis

lightbulb现实痛点步态跌倒与移动监测

医生难以利用可穿戴设备数据准确评估患者在现实场景中的步态变化。

CHI '22'Are They Doing Better In The Clinic Or At Home': Understanding Clinicians? Needs When Visualizing Wearable Sensor Data Used In Remote Gait Assessments For People With Multiple Sclerosis

相邻分类

传感、识别与安全

步态跌倒与移动监测

全部问题

相关论文

RDGait：基于单芯片雷达的复杂室内环境毫米波步态识别系统

NeuralGait：使用智能手机评估大脑健康

LT-Fall：危及生命的跌倒检测与报警系统的设计与实现

'他们在诊所还是在家表现更好': 理解临床医生在可视化远程步态评估中可穿戴传感器数据时的需求，针对多发性硬化症患者

相邻分类

手势姿态感知模型性能与准确性

可穿戴健康设备与日常感知

语音、面部与身体姿态输入

生物特征认证与安全识别

HAR模型鲁棒性、泛化与数据增强

可穿戴健康、活动与行为监测

IMU 惯性感知

移动触控与微手势输入