**5.1 Human motion monitoring**

When wearable electromechanical sensor is mounted on the skin or integrated with textiles, it can real-time monitor human motions including hand, limb, foot, face, and throat. Subtle deformations induced by body activities such as blood pulse flow and respiration, and large deformations related to the body movements such as finger and knee bending can be readily detected. **Figure 5** shows the human motions in daily life detected by CNT-coated auxetic foam strain sensor (AFS) [68]. As **Figure 5a** shows, the foam sensors performed well by dependably detecting the timing, frequency, and magnitude of the impact event and outputting signals in sharp spikes corresponding to the impact events. **Figure 5b** shows the monitoring of the muscle movement during speech by attaching a foam sensor onto a person's neck. When the person repeatedly says the simple words "go," stable signals can observe which timing and pattern corresponded well with the vocal events. Moreover, the wrist pulse has also been successfully monitored by the AFS (**Figure 5c**). A typical pulse waveform is obtained, and the pulse frequency of 76 beats min<sup>−</sup><sup>1</sup> can be calculated. It can also be used to transfer the human intentions of pressing buttons and switches by attaching the AFS directly to the fingertip (**Figure 5d**). **Figure 5e** demonstrates that the AFS can control gesture by wearing on the finger joint because the signal of the foam sensor one by one corresponds to the gesture. **Figure 5f** and **g** shows the schematic and a photograph of the sensor matrix, respectively. **Figure 5h** illustrates the sensing system and a simplified electrical schematic that scan the intersecting points of the sensor's rows and columns and measure the resistance at each crossing point. The plantar pressure distribution can be successfully analyzed with AFS matrix, further extending its fields of application ranging from sports performance and injury prevention to prosthetics and orthotics design. For further example, **Figure 5j**–**n** shows the various barefoot pressure distributions applied by a human right foot (**Figure 5o**), including neutral position, pronation, supination, plantar flexion, and dorsiflexion, which is displayed by the colored contour maps. The in-shoe plantar pressure measurement can also be finished by simply inserting AFS matrix into shoes. It can be anticipated that wearable electromechanical sensor can find a wide range of applications in human motion monitoring, body pressure distribution, and even adjusting sitting posture.

## **5.2 Human health monitoring**

Human health monitoring is based on the continuous monitoring of human motions, especially the pulse and respiration. Wearable electromechanical sensor attached on wrist and chest can be used to detect the pulse and respiratory rate. **Figure 6** shows that graphene film strain sensor can exactly monitor people's pulse and breath rate. Strain sensor are attached on a person's wrist or chest for real-time recording of pulse and respiratory rate signals (**Figure 7a**) [69]. **Figure 6b** shows the collected pulse and respiratory signals, where each cycle represents a pulse or

**91**

even the diagnosis diseases.

The GF of GWF strain sensor can be as high as 103

**5.3 Speech recognition**

**Figure 6.**

**Figure 7.**

*Wearable Electromechanical Sensors and Its Applications DOI: http://dx.doi.org/10.5772/intechopen.85098*

breath. The valleys correspond to the shrinking of the chest, and peaks represent the stretching of the chest. Then, the pulse and breath rates can be estimated to be about 76 and 19 in 60 s, respectively. Three kinds of exhaled breath (simulated diabetic breath, simulated nephrotic breath, and the breath of healthy individuals) are investigated. The obtained response data are analyzed, and the results are displayed in **Figure 6c**. It can be observed that the three breath samples are clearly different. The exhaled breath samples are categorized into three distinguishable clusters without any overlap, which correspond to healthy individuals, simulated diabetic patients, and simulated nephrotic patients, respectively. This demonstrates that wearable strain sensor has high potential for human health monitoring and

*Piezoresistive sensors for human-machine interfaces: (a) smart gloves and (b) robotic controlling.*

*Health monitoring with graphene strain sensor. (a) Photograph of strain sensor mounted on the human wrist, (b) normalized resistance changes of the strain sensor when monitoring wrist pulses and respiratory rate, and (c) PCA analysis of exhaled breath of simulated nephrotic patients, diabetic patients, and healthy people.*

Speech recognition is also based on the monitoring of human motions. When the wearable electromechanical is attached on the throat, it could record muscular movements in order to collect and recognize speech sounds. This is permitted by the fact that the throat muscle exhibits different degrees of stretching or shrinking strains when speaking different words. Due to the tiny changes caused by throat motion, the strain sensor used in speech recognition should have high sensitivity.

higher strains (>7%), and ~35 with a minimal strain of 0.2%, which is suitable for this application. The results show test signal waveforms of all 26 english letters [70]. As expected, the waveforms are unique and repeatable for all letters. Since each

with 2–6% strains, 106 with

*Wearable Electromechanical Sensors and Its Applications DOI: http://dx.doi.org/10.5772/intechopen.85098*

#### **Figure 6.**

*Wearable Devices - The Big Wave of Innovation*

which would be discussed in the following.

**5.1 Human motion monitoring**

beats min<sup>−</sup><sup>1</sup>

adjusting sitting posture.

**5.2 Human health monitoring**

**5. Applications of wearable electromechanical sensor**

Wearable electromechanical sensors can basically detect mechanical signals including pressure and strain. Applications that require monitoring pressure and strain are theoretically can realized by it. Until now, monitoring of human motion and health, speech recognition, gesture recognition, human machine interaction, acoustic waves detection, and even disease diagnosis have been demonstrated,

When wearable electromechanical sensor is mounted on the skin or integrated with textiles, it can real-time monitor human motions including hand, limb, foot, face, and throat. Subtle deformations induced by body activities such as blood pulse flow and respiration, and large deformations related to the body movements such as finger and knee bending can be readily detected. **Figure 5** shows the human motions in daily life detected by CNT-coated auxetic foam strain sensor (AFS) [68]. As **Figure 5a** shows, the foam sensors performed well by dependably detecting the timing, frequency, and magnitude of the impact event and outputting signals in sharp spikes corresponding to the impact events. **Figure 5b** shows the monitoring of the muscle movement during speech by attaching a foam sensor onto a person's neck. When the person repeatedly says the simple words "go," stable signals can observe which timing and pattern corresponded well with the vocal events. Moreover, the wrist pulse has also been successfully monitored by the AFS (**Figure 5c**). A typical pulse waveform is obtained, and the pulse frequency of 76

can be calculated. It can also be used to transfer the human intentions

of pressing buttons and switches by attaching the AFS directly to the fingertip (**Figure 5d**). **Figure 5e** demonstrates that the AFS can control gesture by wearing on the finger joint because the signal of the foam sensor one by one corresponds to the gesture. **Figure 5f** and **g** shows the schematic and a photograph of the sensor matrix, respectively. **Figure 5h** illustrates the sensing system and a simplified electrical schematic that scan the intersecting points of the sensor's rows and columns and measure the resistance at each crossing point. The plantar pressure distribution can be successfully analyzed with AFS matrix, further extending its fields of application ranging from sports performance and injury prevention to prosthetics and orthotics design. For further example, **Figure 5j**–**n** shows the various barefoot pressure distributions applied by a human right foot (**Figure 5o**), including neutral position, pronation, supination, plantar flexion, and dorsiflexion, which is displayed by the colored contour maps. The in-shoe plantar pressure measurement can also be finished by simply inserting AFS matrix into shoes. It can be anticipated that wearable electromechanical sensor can find a wide range of applications in human motion monitoring, body pressure distribution, and even

Human health monitoring is based on the continuous monitoring of human motions, especially the pulse and respiration. Wearable electromechanical sensor attached on wrist and chest can be used to detect the pulse and respiratory rate. **Figure 6** shows that graphene film strain sensor can exactly monitor people's pulse and breath rate. Strain sensor are attached on a person's wrist or chest for real-time recording of pulse and respiratory rate signals (**Figure 7a**) [69]. **Figure 6b** shows the collected pulse and respiratory signals, where each cycle represents a pulse or

**90**

*Health monitoring with graphene strain sensor. (a) Photograph of strain sensor mounted on the human wrist, (b) normalized resistance changes of the strain sensor when monitoring wrist pulses and respiratory rate, and (c) PCA analysis of exhaled breath of simulated nephrotic patients, diabetic patients, and healthy people.*

#### **Figure 7.**

*Piezoresistive sensors for human-machine interfaces: (a) smart gloves and (b) robotic controlling.*

breath. The valleys correspond to the shrinking of the chest, and peaks represent the stretching of the chest. Then, the pulse and breath rates can be estimated to be about 76 and 19 in 60 s, respectively. Three kinds of exhaled breath (simulated diabetic breath, simulated nephrotic breath, and the breath of healthy individuals) are investigated. The obtained response data are analyzed, and the results are displayed in **Figure 6c**. It can be observed that the three breath samples are clearly different. The exhaled breath samples are categorized into three distinguishable clusters without any overlap, which correspond to healthy individuals, simulated diabetic patients, and simulated nephrotic patients, respectively. This demonstrates that wearable strain sensor has high potential for human health monitoring and even the diagnosis diseases.
