IMU Sensor Based Expandable Fall Detection System Design

Ahmet Turan; Duaa Warille

Article Details

IMU Sensor Based Expandable Fall Detection System Design

Authors:

Ahmet Turan | Duaa Warille

Publisher:

Ordu University

Main Topics:

Akış ve Sensör Verileri | Analog Elektronik ve Arayüzler/ Bağdaştıcılar | Gömülü Sistemler | Elektronik | Sensörler ve Dijital Donanım (Diğer) | Tıbbi Robotik

Journal:

Ordu Üniversitesi Bilim ve Teknoloji Dergisi Vol.15 Issue 1, pp.115-127

Document Type:

Article

Publication Date:

6/2025

Document Language:

English

Document ID (Org No.):

2001352233

pISSN:

2146-6440

Keywords:

Abstract:

 Falls and their consequences pose significant health problems affecting individuals of various age groups. Aging individuals are generally weaker, less stable, and slower to react, increasing the likelihood of falls and injuries. Falls are a serious concern, have a significant impact on mobility and quality of life. They also have a significant financial impact on healthcare systems worldwide. The effects of a fall can range from minor bruises, injuries, life-threatening fractures and even fatal conditions. For these reasons, continuous monitoring of the activities of elderly and disabled people has become one of the main goals of telemedicine, and wearable devices have become widespread. The main goal of this study is to develop a system that allows for the precise and automatic detection and monitoring of falls. This approach will generate timely alerts and notifications to quickly inform caregivers or medical doctors. The system created in the study is expandable and can add a large number of sensors. The data transferred from the IMU sensors placed on the patient to the Raspberry Pi is evaluated by software. A fall perception is created when sudden changes occur from the values determined as normal posture levels. Bending and falling are separated. Taking this into account, various falling variations are detected.

 Falls and their consequences pose significant health problems affecting individuals of various age groups. Aging individuals are generally weaker, less stable, and slower to react, increasing the likelihood of falls and injuries. Falls are a serious concern, have a significant impact on mobility and quality of life. They also have a significant financial impact on healthcare systems worldwide. The effects of a fall can range from minor bruises, injuries, life-threatening fractures and even fatal conditions. For these reasons, continuous monitoring of the activities of elderly and disabled people has become one of the main goals of telemedicine, and wearable devices have become widespread. The main goal of this study is to develop a system that allows for the precise and automatic detection and monitoring of falls. This approach will generate timely alerts and notifications to quickly inform caregivers or medical doctors. The system created in the study is expandable and can add a large number of sensors. The data transferred from the IMU sensors placed on the patient to the Raspberry Pi is evaluated by software. A fall perception is created when sudden changes occur from the values determined as normal posture levels. Bending and falling are separated. Taking this into account, various falling variations are detected.

 Falls and their consequences pose significant health problems affecting individuals of various age groups. Aging individuals are generally weaker, less stable, and slower to react, increasing the likelihood of falls and injuries. Falls are a serious concern, have a significant impact on mobility and quality of life. They also have a significant financial impact on healthcare systems worldwide. The effects of a fall can range from minor bruises, injuries, life-threatening fractures and even fatal conditions. For these reasons, continuous monitoring of the activities of elderly and disabled people has become one of the main goals of telemedicine, and wearable devices have become widespread. The main goal of this study is to develop a system that allows for the precise and automatic detection and monitoring of falls. This approach will generate timely alerts and notifications to quickly inform caregivers or medical doctors. The system created in the study is expandable and can add a large number of sensors. The data transferred from the IMU sensors placed on the patient to the Raspberry Pi is evaluated by software. A fall perception is created when sudden changes occur from the values determined as normal posture levels. Bending and falling are separated. Taking this into account, various falling variations are detected.

 Düşmeler ve sonuçları, çeşitli yaş gruplarındaki bireyleri etkileyen önemli sağlık sorunlarını ortaya çıkartır. Yaşlanan bireyler genellikle daha güçsüz, daha dengesizdir ve daha yavaş tepki verirler, bu da düşme ve yaralanma olasılıklarını artırır. Düşme ciddi bir endişe kaynağıdır, hareket ve yaşam kalitesi üzerinde önemli bir etkiye sahiptir. Ayrıca dünya çapında sağlık sistemleri üzerinde önemli bir finansal etkiye sahiptir. Bir düşmenin etkisi, küçük morluklar, yaralanmalar, hayatı zorlaştıran kırıklar ve hatta ölümcül olabilen durumlara kadar değişebilir. Bu nedenlerle yaşlı ve engelli kişilerin aktivitelerinin sürekli olarak izlenmesi tele-tıbbın temel amaçlarından biri haline gelmiş ve giyilebilir cihazlar yaygınlaşmıştır. Bu çalışmanın temel amacı, düşme durumlarının hassas ve otomatik olarak algılanmasına ve izlenmesine imkan tanıyan bir sistem geliştirmektir. Bu yaklaşım, bakıcıları veya tıp doktorlarını hızlı bir şekilde bilgilendirmek için zamanında uyarılar ve bildirimler üretecektir. Çalışmada oluşturulan sistem, geliştirilebilir özellikte olup çok sayıda sensör eklenebilmektedir. Hastanın üzerine yerleştirilen IMU sensörlerden, Raspberry Piye aktarılan veriler yazılımla değerlendirilmektedir. Normal duruş seviyeleri olarak belirlenen değerlerden ani değişiklikler meydana geldiğinde düşme algısı oluşturulur. Eğilme ve düşmeler ayrıştırılır. Bu durum göz önüne alınarak çeşitli düşme varyasyonları tespit edilir.

Article Details

IMU Sensor Based Expandable Fall Detection System Design

Authors:

Ahmet Turan | Duaa Warille

Publisher:

Ordu University

Main Topics:

Akış ve Sensör Verileri | Analog Elektronik ve Arayüzler/ Bağdaştıcılar | Gömülü Sistemler | Elektronik | Sensörler ve Dijital Donanım (Diğer) | Tıbbi Robotik

Journal:

Ordu Üniversitesi Bilim ve Teknoloji Dergisi Vol.15 Issue 1, pp.115-127

Document Type:

Article

Publication Date:

6/2025

Document Language:

English

Document ID (Org No.):

2001352233

pISSN:

2146-6440

Elderly people

fall detection

remote patient monitoring

IMU sensor

Raspberry PiYaşlı insanlar

düşme tespiti

uzaktan hasta izleme

IMU sensör

Raspberry Pi

Issues

Article Details

Authors: Ahmet Turan | Duaa Warille

Publisher: Ordu University

Main Topics: Akış ve Sensör Verileri | Analog Elektronik ve Arayüzler/ Bağdaştıcılar | Gömülü Sistemler | Elektronik | Sensörler ve Dijital Donanım (Diğer) | Tıbbi Robotik

Journal: Ordu Üniversitesi Bilim ve Teknoloji Dergisi Vol.15 Issue 1, pp.115-127

Document Type: Article

Publication Date: 6/2025

Document Language: English

Document ID (Org No.): 2001352233

pISSN: 2146-6440

Issues

Authors:

Ahmet Turan | Duaa Warille

Publisher:

Ordu University

Main Topics:

Akış ve Sensör Verileri | Analog Elektronik ve Arayüzler/ Bağdaştıcılar | Gömülü Sistemler | Elektronik | Sensörler ve Dijital Donanım (Diğer) | Tıbbi Robotik

Journal:

Ordu Üniversitesi Bilim ve Teknoloji Dergisi Vol.15 Issue 1, pp.115-127

Document Type:

Article

Publication Date:

6/2025

Document Language:

English

Document ID (Org No.):

2001352233

pISSN:

2146-6440